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Sterling Gabriel II
I’m a Morehouse finance graduate working in investment-accounting operations at Bank of America, with experience in public finance and fixed-income sales and trading. I’ve contributed to debt-financing proposals, developed two commercial-paper systems adopted by traders and sales, and built 30+ AI-assisted workflows now used by my team. What connects that work is close attention to its financial purpose and the people who rely on it. I carry improvements through review, documentation and teaching, and make time to build relationships beyond my immediate assignment.
Bank of America
IT Business Analyst III · Global Markets Operations · February 2026 — present
In the PAM operations team, I support Corporate Investments by reviewing trade economics and booking instructed transactions, reconciling cash, collateral and positions, monitoring settlements, and investigating discrepancies with trading, operations and technology colleagues. The work spans U.S. Treasuries, repo, Agencies and money markets. I also process cash and income, apply approved pricing updates, prepare FHLB/ATCS journals for independent review, post approved FHLB entries and supply control and audit evidence.
Learning the work closely became a foundation for contributions beyond the assignment. I authored the approved pricing procedure, and my learning notes became a basis for official team procedures. I independently introduced a platform of 30+ AI-assisted Excel/VBA solutions that is used daily by the team, with 800+ logged runs and an estimated 115 hours saved annually. All described solutions passed firm risk review; recurring workflows entered management-approved procedures.
I wrote guides explaining tool logic, dependencies and recovery for colleagues without VBA backgrounds. I train teammates to create and modify their own workflows, build requested tools for other teams, and show colleagues how to develop their own. I also teach weekly in the department’s CTO AI Innovators Lab.
Siebert Williams Shank
Fixed Income Analyst Intern · Sales & Trading · August — December 2025
After my Public Finance summer, I returned in Fixed Income, supporting traders and sales across Commercial Paper, Agencies, Municipals and Treasuries. I developed two distinct Commercial Paper systems that the desk adopted: issuer eligibility and prospective-program capacity analysis, and a Bloomberg-connected ratings history with daily records and change alerts.
Additional work included an Agency redemption model, a repo tracker for planned Treasury and Agency activity, callable municipal-bond databases and trade-documentation requests with Operations and Compliance. I also observed new-issue pricing and allocation, gaining context for the process while keeping that exposure distinct from execution responsibility.
Siebert Williams Shank
Public Finance / Infrastructure Summer Analyst · June — August 2025
Researched municipal and infrastructure issuers and markets using Bloomberg and MSRB EMMA, and contributed research and drafting to RFP responses, pitch decks and offering materials. Additional work included issuance records, deal tombstones and separate green-financing research.
City of Los Angeles
Financial Services Intern · Board of Public Works · June–August 2023 · June–August 2024
During two separate summers at the Board of Public Works, I worked directly with commissioners and reviewed 271 public-sector investment funds for idle balances and data gaps. I researched ordinances, council files and administrative codes, investigated balance-sheet and trial-balance discrepancies, and presented findings to Board leadership. In 2024 I also supported budget analysis during the hiring freeze.
My experience included collaboration with program managers on public-private partnerships and exploration of policy issues involving climate emergencies, petroleum and oil, and forest management. Working with program managers helped me connect the financial records with the programs, operating constraints and public responsibilities around them.
I spent one week of the 2024 internship in LADWP’s Financial Services Office, learning from Ann M. Santilli about its separate Water and Power systems, customer-revenue-supported operations, revenue-bond capital financing, future funding needs and financial-risk oversight. I also helped plan and deliver the Watts community career fair and monitored event funds.
Morehouse Investment Fund
Technology Industry Head · While enrolled at Morehouse
As Technology Industry Head in the Morehouse Investment Fund, I researched company growth drivers and disruptive trends across AI, semiconductors and software. I led construction of a concentrated ten-equity technology portfolio using fundamental and technical analysis, and presented market outlooks and portfolio work, including to BlackRock executives in Atlanta.
The work required me to turn research into a view and then explain that view to an audience. It was a collegiate investment-fund responsibility, distinct from professional portfolio management.
Morehouse Marketing Association
Treasurer · Organization re-establishment year
Managed student-organization budgeting, financial planning and event funding during the association’s re-establishment year.
Lighthouse Mentorship Program
Mentor · October 2024 — May 2025
Offered mentorship to underclassmen, drawing on my academic, leadership and early professional experience.
Academic–Industry Fellowship
McDonald’s-related academic experience · August — December 2023
Academic-industry work involving franchise owners and executives. This is recorded as a fellowship experience, not direct corporate employment at McDonald’s.
The financial responsibilities behind my title.
My role is IT Business Analyst III in Global Markets Operations. I work in the PAM operations team, which primarily supports Corporate Investments. PAM is the investment-accounting ledger: it records the activity that needs to agree with the relevant operational sources. It is not itself the settlement system.
I review trade details against desk instructions before applicable input and booking; reconcile cash, collateral and positions; investigate discrepancies; and follow up on unsettled activity with the responsible trading, operations and technology contacts. The work also includes cash and income processing, approved pricing actions, journal preparation and control reporting. The work includes U.S. Treasuries, repo, Agencies and money markets, alongside mortgage-related investment-accounting participation.
The job requires more than moving data between systems. I need to understand which record I am reviewing, why it differs, what has already been completed and what still needs another person’s attention. Daily checks and clear handoffs help keep that work reviewable. The automation I later initiated grew out of this operating knowledge; it did not replace these assigned responsibilities.
Working close to investment records has taught me to ask what a difference means before trying to clear it. That operating knowledge gave the later automation its purpose: preserve the information and make the next review easier to follow.
Assigned investment-accounting operations in the PAM operations team, primarily supporting Corporate Investments. Trades are booked on the responsible desk’s instructions.
Trade instructions, translated into accurate records.
An instruction needs to retain its meaning when it becomes a system record. Security, portfolio, dates, quantity and monetary details all matter to the subsequent accounting and operational workflow.
I review the instruction and applicable security identifiers, portfolios, trade and settlement dates, quantities, prices, accrued interest, net money, counterparties and settlement details before instructed trade input and booking. I also support the required security and system-setup checks within the approved process. When something does not agree, the next step is clarification with the appropriate contact rather than guessing at the intended trade.
This work connects desk instructions to the records used downstream. My related Treasury booking-file automation prepares a controlled workbook, preserves required mappings and checks for previously prepared items; the person using it still reviews the output and carries out the approved next step.
Knowing the booking process helped me decide which parts of preparation could be automated and which details a person still needed to confirm. The design starts with preserving the desk’s instruction.
Review and instructed trade input within the approved operating process.
Follow an open item through the handoff.
An unsettled item needs enough context for the right person to act. A status alone may not explain whether the issue is a mismatch, a missing record or something requiring another team’s attention.
I monitor unsettled activity using operational reports and reconciliation output, identify open or mismatched items, and prepare trade-log and settlement communications. I route discrepancies to the relevant trading, operations, technology or other responsible contact. This makes the follow-up part of the work rather than treating preparation of a report as the end of the task.
I also developed reporting workflows that select the appropriate business-day sources, organize settlement activity and retain dated output for review. The reporting and draft communications are prepared for a person to check and send, keeping the reviewer in the process.
I’ve learned to make the unresolved part of an item as clear as the completed part. A useful handoff tells the next person why their attention is needed.
Monitoring, investigation and coordination with the teams responsible for resolving unsettled activity.
Keep cash and income information usable.
The cash-processing workflow involves incoming data, working records and differences that need to be explained. My work includes recurring cash-file, manual-load, dividend and income processing.
I review incoming cash and operational information, update the relevant working records, research discrepancies and support the required clearing, matching, offsetting or escalation. That gives me a practical understanding of the relationship between a source file, its format and the record used in the next step.
I used that understanding in additional builds, including FNMA extraction and manual-load formatting, controlled dividend-file ingestion and daily workbook preparation. Those tools organize and validate information for the approved workflow rather than independently moving money.
Working with both the incoming file and the next cash-processing step helped me identify the fields and checks that mattered. That is where the preparation tools began.
Recurring cash-file, manual-load, dividend and income-processing support.
A price update is not finished at the upload.
My operational pricing work covers approved price-change requests, pricing remarks, IDC-related processing, uploads and stale-price remediation. The question is not simply whether a file was produced, but whether the approved action was processed and the remaining work is understood.
I review incoming information and reconciliation output, support approved processing, monitor completion and escalate unresolved items. Separately, I built tools for selecting the appropriate source, comparing current and prior pricing data, identifying missing values and retaining dated review output.
I authored a combined pricing procedure covering price changes, remarks, IDC pricing and stale-price updates, approved by desk management effective May 1, 2026. I also co-authored a later trade-input procedure revision. Writing instructions required me to explain the sequence and review points clearly enough for another colleague to use.
Writing the procedure made me work through the whole sequence, including completion checks and unresolved items. It gave another colleague a way to follow the same operating logic.
Approved operational pricing work and one combined pricing procedure.
Prepare clearly. Keep approval independent.
Journal work needs a clear connection from the operational input to the proposed entry and its review. Preparation, approval and posting are distinct responsibilities.
I prepare applicable FHLB/ATCS journal-entry workbooks and supporting evidence, and draft requests for independent review. I also personally perform FHLB posting under the approved human workflow, then support status communication and completion evidence. That personal duty is separate from what a macro is permitted to do.
My related tools prepare standardized templates and review packages from approved inputs. They preserve required structure and supporting evidence, leaving approval and downstream action with the responsible person. Clear preparation makes the next review easier to follow without merging preparer and approver roles.
A review package should make it easy to trace the proposed entry to its inputs. I designed the preparation around that connection and the independent approval that follows it.
FHLB/ATCS preparation for independent approval; approved FHLB posting is a separate human step.
Investigate the difference, not just the total.
Reconciliation begins when two relevant records do not agree. The difference can involve an unmatched item, an amount, a missing record or stale information, and those are not interchangeable problems.
I review applicable cash and position records, investigate the differences, update comments and support resolution or escalation. My work includes PAM and applicable InTrader reconciliation, alongside other operational sources used in the team’s process. I work from the relevant record and instruction rather than assuming that a difference should simply be adjusted away.
Across my additional workflow builds, I applied the same discipline through source checks, visible unresolved values, consistent output structures and retained evidence. The output should help a person understand the difference and decide what needs attention.
I enjoy the investigative part of this work: tracing an amount back to its source, finding the reason for a difference and explaining what needs to happen next.
Applicable cash, collateral and position reconciliation within my operating responsibilities.
Leave the work ready for the next reviewer.
Operational work has to be understandable after the first person has completed their step. A reviewer needs the relevant output, supporting evidence and a clear status of unresolved items.
I perform beginning-, intraday- and end-of-day checks, prepare operational status communications and control reports, and support audit-evidence provision and data-testing responses. I also prepare regulatory reporting packs for approval. In each case, my contribution is to make the required information available in the appropriate review process.
The same emphasis appears in my automation: required-field checks, missing-file hard stops, duplicate safeguards, standardized output and retained run evidence. These controls make problems visible and preserve a review trail; they do not turn a preparation tool into an approver.
I treat the evidence and the status of the work as part of the handoff. They let a colleague review the result without relying on my memory of how I reached it.
Operational checks and evidence preparation; regulatory reporting packs are prepared for approval.
From learning the operation to building for the team.
While learning my assigned financial workflows at Bank of America, I noticed repeated preparation, cross-application handoffs and opportunities to make the work more consistent. Automation was not part of my formal job description. I originated the idea for the team’s control center and developed the broader capability.
I built the platform with AI assistance using Excel and VBA. The solutions cover controlled file preparation, reporting, cash-input mapping, pricing comparisons, standardized templates and evidence capture. I worked through the business purpose, inputs, expected output and failure conditions rather than treating a working macro as a complete operating solution. Human review, duplicate prevention and explicit checks remained part of the design.
The platform is used daily by the PAM operations team. It has 800+ logged runs, and the documented estimate is approximately 115 annual hours saved. All solutions in the described platform passed firm risk review, and recurring workflows were incorporated into management-approved procedures. I wrote supporting documentation and taught teammates to create their own tools and modify existing ones.
The platform became part of the team’s recurring work. Getting there required learning the operation, carrying the solutions through review and making the logic understandable to colleagues. That follow-through is the part of the contribution I’m most interested in continuing.
30+ solutions across the platform; 800+ logged runs; approximately 115 estimated annual hours saved. Daily use describes the team’s use of the platform, rather than every tool every day.
Build the review into the workflow.
A tool that makes the happy path faster still needs to behave sensibly when a file is missing, an input is incomplete or a record has already been prepared. That was a practical design issue across my operating tools.
I used required-field checks, protected mappings, duplicate prevention, missing-file checks, controlled fallbacks and clean error exits. Some workflows retain dated outputs and run-level evidence. Others deliberately leave an unresolved value visible rather than replacing uncertainty with an apparently complete result. These choices are connected to the particular workflow; they are not one universal checklist applied without context.
All solutions in the described platform passed firm risk review, and recurring workflows entered management-approved procedures. The tools prepare work for people to inspect and carry forward. A draft email is still a draft, and a prepared workbook is not automatic permission to submit, approve or post.
I want a person to be able to tell when a tool cannot finish safely. A clear missing-file message or an unresolved value is more useful than an output that only appears complete.
Workflow-specific checks and human review. Future changes require their own appropriate testing and review.
Turn repeated preparation into a controlled handoff.
Several recurring workflows involved locating the right information, applying the right structure and preparing an output that a colleague could review. The financial meaning and the required format both needed to survive that handoff.
I developed Treasury booking-file preparation that filters the relevant records, excludes previously prepared items, preserves protected mappings and generates a dated review workbook. I also built settlement-reporting workflows that use current, prior and next-business-day sources, organize activity and preserve evidence. Communications are prepared for review rather than sent unattended.
These builds sit inside the broader team platform and address repeated preparation work. The design uses explicit checks and visible failures to avoid presenting an incomplete source set as a ready output. The reviewer still owns the check and the approved downstream step.
The task was to preserve the financial information while taking repeated preparation out of the way. That required knowing both the source and what the receiving workflow expected.
Preparation of files, reports and draft communications for a person to review and carry forward.
A source file, made ready for the next cash step.
My cash-processing work provided the context for a recurring FNMA file-preparation task. Information needed to be extracted and placed into the structure used for a manual load.
I developed extraction and formatting with source validation, required-field checks, field ordering and dated review-ready output. The point was not simply to move values into Excel. The resulting template needed to retain the required information and make missing inputs visible before it entered the approved workflow.
This build sits alongside my personal cash-file, manual-load, dividend and income support. It is a specific example of learning a recurring process and improving the preparation around it, with the next action remaining part of the human operating workflow.
This was a specific improvement I could make because I understood the cash workflow around it. Required fields, ordering and visible missing inputs all came from what the next step needed.
FNMA file preparation within cash-processing and investment-accounting operations.
Compare the sources before preparing the change.
Pricing preparation involves source selection as well as comparison. A current-looking file is not useful if it is incomplete or if the relevant prior information is lost.
I developed workflows that select qualifying sources, compare current and prior data, deduplicate security identifiers, organize additions and removals, flag missing prices and preserve a dated review trail. Stale-price preparation uses a latest-valid-date fallback and stops when the required source conditions are not satisfied.
The outputs support operational review and approved pricing work. Combined with procedure documentation, they give a colleague a more consistent starting point and a clearer record of what needs attention.
I organized the comparison around changed and missing values so the reviewer could begin with the items needing attention. Keeping the dated source trail lets them investigate the reason for a change.
Source comparison and file preparation for approved operational pricing actions.
Make the work understandable without its author.
My documentation began while I was learning the operation. I took detailed notes to understand the sequence, purpose and dependencies of unfamiliar work. Some of those notes became a basis for official team procedures.
I later documented individual automations: what the tool does, its logic, guardrails, expected messages, dependencies, edge cases and recovery steps. I included code explanations and instructions for colleagues without a VBA background. Separately, I authored a combined pricing procedure approved effective May 1, 2026 and co-authored a trade-input revision dated May 8.
These are related but distinct contributions. Learning notes preserve understanding; approved procedures describe the operating sequence; tool guides explain how to use and change a particular build. Together, they support continuity when the original developer is not the person doing the work.
Writing the explanation is a way of checking my own understanding. It also gives someone else a place to start when they need to use the process, cover an absence or make a change.
One combined pricing procedure approved May 1, 2026; a co-authored May 8 trade-input revision; separate learning notes and tool guides.
Share the ability to build, not just the finished tool.
Once a team starts using a tool, there are two different needs: being able to run it today and being able to adapt the work later. I wanted colleagues to have a starting point for both.
I taught my own teammates to use, maintain and run workflows in my absence, and to create their own AI-assisted Excel/VBA tools and modify existing ones when needed. That teaching sits alongside guides that explain purpose, logic, dependencies and recovery for readers without a VBA background. On other teams, I also supplied requested builds and taught colleagues to create workflows for their own processes.
The contribution is not only the finished file. It includes making the approach more accessible: understanding the workflow, identifying a useful task to improve, and seeing where validation and review belong. I also teach weekly in the department’s CTO AI Innovators Lab after being asked because of my tool-building work.
I enjoy seeing someone begin to approach a recurring problem as something they could improve. The documentation gives them a reference after the conversation, and the teaching gives the reference a practical starting point.
Own-team teaching covers use, maintenance, creation and modification. Cross-team support and departmental teaching are additional contributions.
Get to know the work beyond your own desk.
I take an interest in colleagues and in what their part of the business actually does. At SWS, that meant meaningful working relationships and friendships across Sales & Trading, Corporate Finance and Public Finance / Infrastructure. At Bank of America, it has also led to opportunities to help other teams.
At Bank of America, I’ve built workflows and implemented VBA for other teams at their request, supplied reusable AI prompts and taught colleagues to create tools for their own processes. One contribution was a reusable PDF-to-Excel design prompt. At SWS, I also created deal tombstones at Corporate Finance colleagues’ request, separately from the Public Finance tombstones. The contributions started with understanding what the other team needed.
Those builds are outside my assigned operations duties. But the relationships are not defined by the builds: I also seek conversations to understand people’s work, learn about other businesses and find sensible ways to contribute.
I want to understand the broader business and the people doing its work. Sometimes that creates a clear opportunity to help; the interest in the person comes with it either way.
Internal working relationships, requested contributions and teaching across business lines.
Bring practical experience into the AI discussion.
The tools I built led to a personal invitation to the department’s small-group AI Innovators forum and to being asked to teach. My contribution is grounded in what I have actually developed and used in an operating setting.
I teach weekly in the CTO AI Innovators Lab, sharing practical AI applications and how colleagues can apply them. Separately, I participate in a departmental AI working group with leaders and colleagues experienced in using AI and building tools. We discuss ideas, development progress and review and approval steps; projects generally remain with the proposing colleague unless they involve multiple teams.
Weekly teaching provides a recurring setting to share practical lessons from my tool-building work. The separate working group gives me contact with other colleagues’ ideas and development questions. Together, they let me contribute what I have learned while continuing to learn from the wider department.
The exchange is useful in both directions. I can share what I’ve learned from building in an operating setting and hear how colleagues are approaching different problems.
Weekly departmental teaching and separate working-group participation, alongside my assigned operations role.
Turn issuer information into a financing question.
The desk was interested in corporations with long-term debt ratings but no current Commercial Paper program or short-term rating. The useful question was which companies could be potential program candidates, and what their ratings and liquidity information suggested about prospective capacity.
I developed an AI-assisted, Bloomberg-connected tool that assembled issuer information in 300-ticker batches. It mapped long-term ratings to potential short-term tiers, calculated tier splits and weights, and combined the ratings view with liquidity inputs including revolvers, accounts receivable and working capital. The resulting screen supported internal issuer eligibility, liquidity and program-capacity analysis.
Traders and sales adopted the tool. It brought information relevant to a financing opportunity into a usable analytical workflow, rather than leaving the work as a list of names or disconnected Bloomberg fields. This was separate from the ratings-history system I also developed for the desk.
The financial question shaped the technical work. Ratings needed to be considered with liquidity and prospective capacity, and the output had to be useful to the traders and salespeople investigating an issuer.
Origination analysis using potential rating tiers and prospective capacity estimates. Official ratings and financing decisions remain with the responsible institutions and desk.
Give the desk a history it can keep using.
A current rating answers one question. A retained history can also show what the rating was at a different point in time and when it changed. That distinction mattered to how traders and sales could use the information.
I developed the Commercial Paper ratings-history system using Bloomberg API data across Moody’s, S&P and Fitch from 1971 onward. It retains dated daily records, appends updates automatically and alerts traders and sales to rating changes. The history also supports comparison of historical trading levels with the ratings in effect at the time. That comparison is one use of the system, alongside ongoing monitoring and retention.
Traders and sales adopted the system, and I refined the workflow around their desk needs. Their feedback gave the work a practical direction: retain the history, keep the daily record current and make changes visible to the people using it. Alongside the separate prospective-program tool, it addressed both ongoing monitoring and a different set of financing questions.
Retaining the date and context made the information useful beyond the next refresh. The desk could monitor changes as they occurred and return to the record when investigating an earlier point in time.
Bloomberg API ratings history from 1971 onward, with availability varying by issuer and agency; daily records and change alerts for desk analysis.
Put issuance and redemptions in the same view.
On the Agency desk, I built a redemption model covering FNMA, GNMA and FHLMC securities. The purpose was to bring issuance and redemption information into one view, with the coupon and call characteristics needed to understand the securities behind the totals.
I built the model in Excel using Bloomberg exports. It combines issuance, redemptions, net issuance, coupon and call measures, outstanding callable bonds and charts. Organizing the measures together makes it possible to examine how new supply and redemptions relate, with call characteristics alongside the broader view.
The finished Excel model combines the measures and charts in a single analytical view. It complements the repo tracker’s focus on funding economics, while serving a different purpose from the transaction-record database I created in Public Finance.
Looking at issuance alongside redemptions makes net supply visible. Adding coupon and call measures connects that broader view with the characteristics of the securities behind it.
An Excel model using Bloomberg exports, covering GSE and agency securities. GNMA is a government agency.
See funding cost alongside income and exposure.
I originated and built the Agency team’s first repo tool for planned Treasury and Agency activity. The purpose was to organize the relationship between borrowings, financing costs, income and counterparty exposure.
The model connected total and current borrowings with counterparty exposure, interest income, funding costs and annualized net carry. It organized active and completed activity, weighted averages and counterparty statistics. I refined it directly with traders and sales around the planned Treasury and Agency activity.
The completed tracking and analysis template brought the planned activity’s borrowing, income, funding-cost and counterparty measures together. It made net carry intelligible alongside the inputs producing it, rather than presenting a return figure without its funding context.
The income figure needed its funding context. Bringing costs, borrowings and counterparty exposure into the same model made the relationships behind net carry easier to examine with the desk.
A model for planned Treasury and Agency repo activity, refined with traders and sales. The account describes the build and analysis, not a live funding book or realized P&L.
Make a client question easier to investigate.
In Municipal Sales & Trading, a request about callable bonds requires more than knowing the issuer. Call features, maturity and structure change which securities are relevant to the inquiry.
I built databases with the Municipal Sales & Trading team that organized securities by call features, maturities and structural characteristics. The records included issuer and security identity, bond type, insurance, ratings and sinking-fund start dates, supporting screening in response to client inquiries.
The databases gave Municipal Sales & Trading an organized basis for investigating securities by call features, maturity and structure when responding to inquiries. The usefulness was in how readily the relevant characteristics could be brought together for the desk’s review.
The client inquiry gave the data its organizing question. Call dates, maturity, insurance and sinking-fund details mattered because they helped the desk identify which securities deserved a closer look.
Database development with Municipal Sales & Trading to support client inquiries.
Bring the supporting records together.
My Fixed Income experience also included helping address FINRA documentation requests. The contribution was in the underlying trade records and the coordination needed to provide them.
I retrieved and validated trade documentation with Operations and Compliance. That work required attention to the records being requested and cooperation with the functions responsible for the response, rather than treating regulatory work as separate from everyday operating evidence.
The work supported the firm’s response by bringing together requested trade documentation and checking the records with Operations and Compliance. My part was the retrieval and validation work needed for that response.
This work showed me why source records need to remain understandable beyond the immediate transaction. The next person inspecting them may be answering a different question.
Retrieval and validation of requested trade records with Operations and Compliance.
See how a financing reaches the market.
During my fixed-income experience, I observed the new-issue pricing and allocation process from pre-pricing through deal day. That gave context to how a financing develops beyond the initial materials.
I followed issuer meetings and deal-room activity, intraday price and yield revisions, retail and institutional order periods and allocation decisions. My role was observational: I was learning how the participants, information and sequencing fit together, not deciding price or allocation.
That exposure complements my direct issuer research and the tools I developed for desk analysis. It helped connect the information being prepared to the market process it can support.
Following the process gave context to the research and analytical work I could contribute directly. I could see how timing, changing information and communication mattered as pricing and orders developed.
Firsthand observation of new-issue pricing and allocation from pre-pricing through deal day.
Research that contributes to a financing proposal.
I supported the Southeast Public Finance team as a Public Finance / Infrastructure Summer Analyst in New York. The work connected issuer and market research to materials used in municipal and infrastructure debt proposals.
I researched issuers and market conditions using Bloomberg and MSRB EMMA, and contributed research and drafting to the team’s RFP responses, pitch decks and offering documentation. I also studied municipal bond structures and observed pricing discussions with issuers and bankers. Research and writing were performed within the team’s review and deadline process.
The research and drafting became part of the Southeast team’s debt-financing proposal materials. Working within its review process gave me experience connecting issuer information, bond structures and market conditions with a proposal bankers needed to communicate. I also created issuance records and deal tombstones and prepared separate green-financing research.
This connected my earlier public-sector work with capital markets. I was learning about an issuer’s services, resources and bond structure, then contributing that research to the team’s explanation of a financing proposal.
Personal issuer research and contributions to research and drafting within the Southeast Public Finance team’s financing materials.
Organize the transaction record.
Alongside issuer research and material preparation during the Public Finance / Infrastructure summer, I worked on transaction-related information and presentation materials.
I created an issuance database and deal tombstones. I also gained experience with Ipreo in connection with new-issue pricing support. These activities gave me further context for the information used around a financing and the way completed or proposed work is represented.
The issuance database and deal tombstones organized transaction information for the Public Finance team. Using Ipreo also gave me exposure to the information supporting new-issue pricing work. These assignments complemented my issuer research and contributions to financing materials.
These assignments put me close to the way financing work is recorded and presented. They complemented the issuer research and drafting I contributed to the team’s proposals.
Issuance records, deal tombstones and Ipreo-related pricing support during the Public Finance / Infrastructure internship.
Research a developing financing theme.
A separate Public Finance research presentation explored EV investment and energy or sustainability-related bond-financing themes. It sat alongside, rather than replaced, my work on the team’s financing materials.
I researched and presented the themes, connecting an interest in emerging industries to questions about financing. The work gave me an additional way to examine how a sector’s development can create financial questions for institutions and markets.
I prepared a research presentation connecting EV investment and energy or sustainability themes with bond-financing questions. It was a chance to bring my interest in developing technologies into the Public Finance setting and explain the theme in financial terms.
I was interested in how a developing industry creates financing questions. The presentation let me explore that connection within public finance, alongside the company research I had done at Morehouse.
A separate research presentation during the Public Finance / Infrastructure internship.
Examine how public resources are accounted for.
I worked in the City of Los Angeles Board of Public Works as a Financial Services Intern during the summers of 2023 and 2024, returning for the second summer. I worked directly with commissioners and attended Board meetings.
I reviewed 271 public-sector investment funds for idle balances and data gaps. I also researched ordinances, council files and administrative codes, investigated balance-sheet and trial-balance discrepancies, and presented findings to Board leadership. Reading the financial record alongside the governing material gave the review a clearer institutional context.
The work brought together financial investigation, research and communication with the people responsible for the institution. In my second summer, I also supported budget analysis during a hiring-freeze and lean-budget period. My contribution was to the review and explanation of the information, not the investment or budget decision itself.
Working with commissioners connected the records I was examining to the people responsible for public resources. Presenting the findings meant understanding the information well enough to explain its significance.
Two separate summer internships, 2023 and 2024. The 271-fund figure covers the recorded experience in aggregate.
Understand the institution behind the financial work.
During the 2024 internship, I supported budget analysis while the City was working within a lean-budget and hiring-freeze environment. The assignment made the organizational context around the numbers especially important.
Beyond the fund review, I collaborated with program managers on public-private partnerships and explored Public Works policy issues involving climate emergencies, petroleum and oil, and forest management. These were different parts of the internship: budget support, collaboration with program managers and policy exploration, rather than a single financing transaction.
The breadth gave me context for how public financial work connects with program needs and policy questions. It complemented my research into ordinances and council files and the financial findings I presented to Board leadership. I carried that interest in understanding the institution into my later municipal and infrastructure research at Siebert Williams Shank.
The conversations with program managers gave the financial records an institutional setting: the programs involved, the constraints they faced and the public responsibilities around them.
Budget-analysis support, program-manager collaboration and policy research during the City internship.
Learn how essential services are financed.
Within my 2024 City of Los Angeles internship, I spent exactly one week in LADWP’s Financial Services Office. It was an opportunity to understand the financial organization behind essential water and power services, not a separate employment role.
During that week, I learned from Ann M. Santilli about the separately operated and financed Water and Power systems, their self-supporting customer-revenue model, revenue-bond capital financing, funding forecasts and risk oversight. I connected those conversations with my broader public-sector finance experience, while keeping the one-week learning assignment distinct from the operating responsibilities of the office.
The visit added financing context to the public-sector fund review and budget work I was doing. It helped connect the institutional purpose of the services with the revenues and capital requirements behind them. That was a useful foundation for my subsequent issuer and infrastructure research in Public Finance.
The week helped me connect essential services with the revenues and long-term capital they depend on. It added a concrete institutional example to the public-finance questions I later encountered at SWS.
Exactly one week in LADWP’s Financial Services Office during the 2024 City internship; learning about financing, forecasts and risk oversight.
Support opportunity beyond the financial record.
My Los Angeles internship included helping plan and deliver a community career fair in Watts, intended to expand local access to employment opportunities.
I supported event planning and delivery and monitored event funds. This required practical coordination and financial follow-through alongside the fund-review and budget-support work in the internship.
The experience gave me another way to contribute to the institution’s work with the community. It also connected financial responsibility with the people the activity was meant to serve.
The fair put the purpose of the activity close to the work of delivering it. Planning and tracking funds were practical ways I could help create access to career opportunities in the community.
Event planning, delivery support and tracking event funds for the Watts career fair.
Develop a view, then make it understandable.
While enrolled at Morehouse, I served as Technology Industry Head in the student investment fund. My research focused on company growth drivers and disruptive trends across AI, semiconductors, software and technology conglomerates.
As Technology Industry Head, I led construction of a concentrated ten-equity technology portfolio using fundamental and technical analysis. I presented market outlooks and portfolio work, including to BlackRock executives in Atlanta. That required moving beyond collecting facts to explaining an investment view and the information behind it.
This experience gave my interest in companies and markets a practical academic setting. It also required communication: the analysis had to be understandable to an audience, not only to me.
Explaining the portfolio forced me to turn company research into a view someone else could question. I enjoyed connecting growth drivers and industry changes with the reasoning behind that view.
Collegiate research, portfolio construction and presentation as Technology Industry Head in the Morehouse Investment Fund.
Help someone else find their footing.
From October 2024 to May 2025, I served as a mentor in the Lighthouse Mentorship Program in Atlanta, working with underclassmen.
I offered academic and career mentorship to underclassmen, drawing on what I was learning through Morehouse, student leadership and early professional experience. It was an opportunity to make that experience useful to someone still finding their direction.
The role gave me a regular setting for sharing guidance with students earlier in their path. It was a different form of contribution from investment research or organization budgeting, but it drew on the same willingness to make time for another person.
I value the time spent understanding where another person is in their own development. Advice becomes more useful when it starts with the question they are actually facing.
Academic and career mentorship to underclassmen through Lighthouse, October 2024–May 2025.
Connect financial statements to valuation.
My Finance Academy capstone material on General Mills connected company understanding with introductory valuation work. It covered business segments, historical financial information and published analyst forecasts.
The academic material included illustrative DCF, trading-multiples, precedent-transaction and WACC work. This gave context for how operating assumptions and discount rates relate to a valuation rather than treating a multiple as an answer by itself.
The capstone connected company research and financial information with the mechanics of valuation in an academic setting. It provided a foundation for understanding why forecasts, comparables and discount rates need to be considered together.
The material helped connect a company’s operating assumptions with the mechanics of valuation. I want to build on that academic foundation through deeper hands-on modeling practice.
Academic material using historical financial information, published forecasts and illustrative valuation. The individual modeling contribution is not established by the available source.
Build a reference you can return to.
My independent learning in applied AI developed into The Intelligence Stack, an extensive reference covering foundations, systems, governance and practice.
I created the 1,975-page, 215-chapter reference to organize the material into something that could be revisited rather than left across disconnected conversations and notes. The project reflects the same interest in structure that appears in my workflow documentation and ongoing learning.
The material became a single organized reference spanning foundational concepts, systems, governance and practical use. Bringing it together gave me something to revisit and extend instead of repeatedly reconstructing what I had already studied.
Organizing the reference gave me a way to return to a subject without reconstructing every previous conversation. That instinct also appears in how I document processes and tools.
An independent reference created with AI assistance: 1,975 pages across 215 chapters.
Put financial follow-through behind student activity.
I served as Treasurer of the Morehouse Marketing Association during the organization’s re-establishment year.
My work included student-organization budgeting, financial planning and event funding. The responsibility was to attend to the financial side of the association’s activities, alongside the contributions of the rest of the organization.
This was practical financial responsibility within a student organization. It complemented the investment research I was doing in the Morehouse Investment Fund and the mentorship I provided through Lighthouse.
The financial planning had an immediate purpose: supporting the association’s activities. It was a practical complement to the company research I was doing in the Investment Fund.
Budgeting, financial planning and event funding for the student association during its re-establishment year.
Learn through contact with industry.
From August to December 2023, I participated in an academic–industry fellowship in Atlanta involving McDonald’s franchise owners and executives.
The experience included presentations and support for student career programming. It provided another setting to communicate with business professionals and contribute to activities connecting students with industry.
The fellowship connected student career programming with industry participation and gave me another setting to present to business professionals. It broadened my experience beyond the classroom while keeping me involved in activities useful to other students.
I valued the contact with people working in different parts of a business and the chance to help connect other students with industry.
An academic–industry fellowship involving franchise owners and executives, August–December 2023; separate from formal employment.
Give recurring research a repeatable workflow.
I created and scheduled four automated daily newsletters using Claude, covering AI, fixed income and rates, mortgages, and broader markets.
The project covers the workflow from source gathering through delivery. It gives recurring research a structure rather than requiring the same setup from scratch each time. The topics connect my interests in markets and applied AI, but remain separate streams with different information needs.
The four streams give recurring research a defined collection and delivery workflow. Keeping the subjects separate makes it easier to revisit the information relevant to each area without rebuilding the same setup every day.
The recurring workflow supports a habit I want to sustain: staying informed across markets and applied AI. The sources and interpretation still need attention even when collection and delivery have a repeatable structure.
Four independent research and learning workflows created and scheduled using Claude.
Make a professional record worth reading.
Role Robot began as an evidence-based way to compare opportunities with my actual experience, distinguish explicit from implied requirements, identify gaps and prioritize fit. CASE and LandingPin explore how a professional profile can help someone follow the work behind a résumé.
I have developed the project through repeated source review, factual corrections and comparisons of how the same experience is represented. A central lesson was that holding the right facts does not automatically make the writing useful. The account also needs to preserve ownership, purpose, the people involved and the significance of the contribution.
This profile brings the professional record into one place: work stories with context, related evidence and selected questions about how I approach the work. The editorial choices preserve individual contribution, team authorship and the distinction between an accomplished result and an area I’m still developing.
I want the detail to make the person clearer. The choices about what to include, how to attribute it and where to offer more context matter as much as collecting the facts.
Independent development of an evidence-led professional profile and a separate role-matching and decision-support method.
Why finance and markets?
Business interested me before I knew which part of finance I wanted to work in. Growing up, Shark Tank and HGTV made ownership, property and investment tangible. I began studying markets more deliberately in my senior year of high school, then built on that interest at Morehouse.
The work since then has given it direction. In Los Angeles, I examined public financial records; at SWS, I contributed issuer research to financing proposals and developed analysis for fixed-income desks. I now work with the records and controls behind investment activity. I enjoy finding out what a number means for the institution using it: whether that’s an issuer’s liquidity, the cost of funding a position or a difference that needs to be reconciled. I want to keep developing the judgment behind those questions.
What should someone understand beyond your job title?
My title is IT Business Analyst III, and my day-to-day work is in Global Markets Operations. In the PAM operations team, I support Corporate Investments through instructed trade booking, reconciliation, settlement monitoring, cash and income processing, approved pricing updates and journal work. When information doesn’t agree, I investigate it with the relevant trading, operations or technology contact.
Understanding those responsibilities closely gave me the starting point for the automation I introduced beyond my assignment. I could see which details had to survive a handoff, where the review belonged and which repeated preparation steps could be improved. The financial work, the additional builds and the teaching are connected: I learn the process, take responsibility for my part, and look for ways to make the team’s work easier to carry forward.
How do you become useful in unfamiliar work?
I want to understand what each input represents, who uses the output and what should happen when the information doesn’t agree. I take detailed notes and work through the process until I can explain it in my own words. That helps me ask more useful questions as well as remember the steps.
At Bank of America, some of those learning notes became a basis for official team procedures. I later authored the approved pricing procedure and wrote guides for the tools I developed. The notes became useful beyond my own learning because they explained the work well enough for someone else to follow. I may notice a repetitive step early, but I want to understand its purpose before deciding how to change it.
How did your additional automation work begin?
I noticed the opportunity while learning the operation. Recurring preparation and comparison tasks involved moving between applications, finding the right sources and rebuilding familiar formats. I understood why the output mattered and wanted to make that preparation more consistent for the team.
I originated and built the team’s first automation platform beyond my assigned duties: 30+ AI-assisted Excel/VBA solutions covering work such as Treasury booking files, cash processing, settlement reporting and pricing comparisons. I kept duplicate safeguards and human review in the workflows, documented them and carried the solutions through firm risk review. The platform is now used daily, with recurring workflows in management-approved procedures. Teaching teammates to create and modify their own tools was part of carrying that work forward.
What makes a system useful rather than merely impressive?
It has to answer a question someone actually has. With the Commercial Paper desk, that question was whether a corporation with long-term debt ratings but no CP program or short-term rating could be a prospective issuer, and what capacity its ratings and liquidity might support.
I developed a Bloomberg-connected tool that brought those inputs together, including revolvers, receivables and working capital. Traders and sales adopted it for their analysis. Understanding the financing question guided the build. In operations, the same attention to the user means making missing information visible, preserving the details they need to check and explaining the next step. A useful system should leave someone better equipped to do their work.
How do you use AI without giving up responsibility for the work?
I use AI to help turn an understood problem into something I can build. Copilot, ChatGPT and Claude are part of my broader learning and development practice. In my professional Excel/VBA work, AI assistance helps with development; the finished workflow can be a conventional tool with no AI model running inside it.
I remain responsible for understanding the financial process, specifying the output, inspecting the result and preserving the required controls. Duplicate safeguards, human review, documentation and firm risk review are concrete parts of that responsibility. The interesting part is deciding what the tool needs to do and knowing whether it does it—not simply producing code.
What kind of relationships do you build at work?
I enjoy getting to know colleagues, including people whose work is outside my assignment. At SWS, I built working relationships and friendships across Sales & Trading, Public Finance and Corporate Finance. I was interested in the people themselves and in how their businesses worked.
At Bank of America, that interest also creates opportunities to collaborate. I’ve built tools at other teams’ request and taught colleagues how to develop workflows for their own processes. Those are ways I can contribute when I have the capacity. I also value the conversations that don’t turn into a project. Being engaged in an organization means knowing more about the people around me than what I need from them for my next task.
What did the Commercial Paper tool actually help the desk do?
It helped the Commercial Paper desk investigate potential issuers: corporations with long-term debt ratings but no current CP program or short-term rating. The desk needed a way to consider both a potential short-term rating tier and the liquidity information relevant to prospective program capacity.
I developed an AI-assisted, Bloomberg-connected tool that worked in 300-ticker batches. It mapped long-term ratings to potential short-term tiers and combined revolvers, accounts receivable and working capital in the capacity analysis. Traders and sales adopted it. The output gave them an organized starting point for origination analysis; official ratings, credit approval and any decision to launch a program remained outside the tool and my responsibility.
Why is the ratings-history system a different project?
The ratings-history system gave the Commercial Paper desk a record it could keep using over time. I developed it with Bloomberg API data from Moody’s, S&P and Fitch, including history from 1971 onward. It retains dated daily updates and alerts traders and sales to rating changes.
The desk adopted it for monitoring and could also compare historical trading levels with the ratings then in effect. I refined the workflow with their feedback. It serves a different need from the prospective-program tool: one helps investigate potential issuers and capacity, while the other preserves issuer-credit history and makes changes visible. Both required understanding how traders and sales would use the information after it was retrieved.
What do you teach colleagues to do?
With my own team, I teach colleagues to use and maintain the workflows, create their own AI-assisted Excel/VBA solutions and modify existing tools when needed. The guides explain purpose, logic, dependencies and recovery for colleagues who may not have a VBA background. They can return to that explanation after a demonstration.
I’ve also built requested tools for other teams and shown colleagues how to develop workflows around their own processes. Separately, I teach weekly in the department’s CTO AI Innovators Lab. I enjoy helping someone see how a recurring problem could be approached differently, then giving them a practical starting point for trying it themselves.
How did your work move beyond a personal project?
At Bank of America, it took work beyond development. I carried the solutions through firm risk review, documented their logic and recovery steps, and taught colleagues how to use, maintain, create and modify workflows. The PAM operations team uses the platform daily, and recurring workflows were incorporated into management-approved procedures.
At SWS, traders and sales adopted both Commercial Paper systems. Their needs helped shape the work, including the ratings-history workflow I refined with their feedback. In both settings, the result had to be understandable and useful when someone else opened it. That changed what I considered part of delivery.
What do the 800+ runs and 115-hour estimate mean?
The 800+ figure is a count of logged platform runs. The approximately 115 hours is a documented estimate of annual time savings, rather than a measured total already realized. They describe different things: recorded use and estimated capacity returned to the team.
I consider them alongside the operating result. The platform contains 30+ AI-assisted Excel/VBA solutions and is used daily by the PAM operations team. Its solutions passed firm risk review, and recurring workflows entered management-approved procedures. That combination of use, review and integration tells you more about the contribution than either number alone.
Why put so much attention into documentation?
My first notes were for learning: what the process was doing, what depended on what, and what I needed to check. Some became a basis for official team procedures. Later, I authored the combined pricing procedure and co-authored a trade-input revision.
The tool guides have another job. They explain what a build does, how its logic works, what it depends on and how to recover when the expected result doesn’t appear. Writing those explanations makes me examine my own understanding. It also gives colleagues something useful to return to when they run a workflow, cover an absence or begin making a change.
How does public finance fit into your story?
My interest in public finance started with the institution behind the financial record. Across two summers in Los Angeles, I worked directly with commissioners, reviewed 271 public-sector investment funds and investigated financial-statement discrepancies. A week in LADWP’s Financial Services Office added context on the separate Water and Power systems, revenue-bond capital financing and future funding needs.
At SWS, I built on that foundation by researching municipal and infrastructure issuers and contributing research and drafting to the Southeast Public Finance team’s RFP responses, pitch decks and offering documents. I could connect the information in a proposal with an institution’s services, resources and financing needs. That remains part of how I approach a financial question.
What did you learn through student leadership?
The Morehouse Investment Fund gave me practice developing and explaining an investment view. As Technology Industry Head, I researched technology companies, led construction of a ten-equity collegiate portfolio and presented market outlooks. The analysis had to hold together when I explained it to an audience.
The Marketing Association asked for a different kind of follow-through: budgeting, financial planning and event funding during its re-establishment year. Through Lighthouse, I offered academic and career mentorship to underclassmen. I valued having several ways to contribute—through analysis, practical financial responsibility and time spent helping another student think through a next step.
Why is New York the next step you want?
My time at SWS made New York a concrete choice. I enjoyed being close to markets and financing work, learning from people across different businesses and building relationships through the conversations around that work. It’s an environment where I want to keep developing.
I’m currently based in Charlotte and planning to relocate to Brooklyn. I’m looking for a team where I can deepen my financial exposure, contribute from the experience I’ve already built and develop stronger judgment through the work itself. The role and the people I’ll learn from matter to that decision.
What would you bring to a new team immediately?
I’d bring experience connecting financial information to its use: issuer research for financing proposals, analytical systems adopted by traders and sales, and recurring cash, position, pricing and trade-record responsibilities in investment operations. Those experiences give me several points of entry for learning a new team’s work.
I’d also bring the willingness to carry an improvement through the less visible parts of delivery. At Bank of America, that has meant review, procedures, practical guides and teaching alongside the build. I want to become dependable in my own responsibilities, understand how colleagues’ work fits together and contribute where I can be useful.
Where are you looking to develop next?
I want more sustained experience with the analysis and judgment behind markets and financing decisions. Issuer research, desk-adopted analytics, collegiate company research and investment-accounting operations have given me a foundation I want to deepen.
The next step is to develop the particular products, analytical methods and decision context of the team I join. I’m interested in work where I can contribute now and keep stretching: understand the business more closely, form a better-supported view and learn how experienced colleagues evaluate it. My ability to learn unfamiliar operations and carry improvements into use is something I can bring to that development.
How do you know when work is ready to hand over?
I want the next person to be able to understand what was prepared, what was checked and what still needs attention. That means the output preserves the intended information, incomplete inputs are visible and the instructions explain what to do when the expected result doesn’t appear.
In my tools, that has led to required-field checks, duplicate safeguards, dated outputs and recovery guidance. In operating work, it means clear comments, supporting evidence and an explicit status for unresolved items. I judge the handoff from the position of the colleague receiving it: can they inspect the work and take the next step without reconstructing what I meant?
What do you build outside your assigned work?
I created The Intelligence Stack, a 1,975-page, 215-chapter applied-AI reference, and four scheduled daily newsletters using Claude covering AI, fixed income and rates, mortgages, and broader markets. Each project gives recurring learning a structure I can return to.
Role Robot explores how to compare actual experience with an opportunity’s requirements, surface gaps and make a better-informed choice. CASE and LandingPin extend my interest in understanding and presenting the work behind a professional record. I enjoy organizing information until it becomes useful beyond the conversation or note where it started. These projects are independent of my employers’ systems.
What is the idea behind your LandingPin?
I wanted a place where someone could follow the work behind my résumé. A concise introduction can tell you what I’ve done; the next click should help you understand the question I was working on, my contribution and the people who used the result.
I also wanted room for perspective. The way I learn, what I find interesting and how I get to know colleagues are part of the professional someone would be hiring. The stories and questions here are meant to make that person easier to understand and give us more to talk about.
How do relationships and technical work reinforce each other?
A conversation can reveal something about another person’s work that I wouldn’t see from my own desk. At Bank of America, colleagues have asked me to build workflows for their teams; I’ve also taught them how to create tools around their own processes. Understanding the problem and the person using the result makes that help more useful.
At SWS, my cross-business relationships also led to requested Corporate Finance deal tombstones alongside my desk work. I enjoyed learning about the different businesses, and I still value the friendships and conversations for their own sake. Technical help is one way I contribute within those relationships. It doesn’t account for everything that makes them worthwhile.