AI Training Role for Finance Experts (Investment, Corporate, FP&A, Valuation, Credit,Treasury, Risk)

*Fully Remote Opportunity* With the option to undertake as many, or as few hours as you would like (8-10 per week a miniumum)

This is not a traditional finance role. You will be helping build better AI by putting your knowledge to work in a structured, flexible, fully remote environment. The work is long form and self directed, and clear written reasoning matters as much as technical depth.

Responsibilities:

• Evaluate how frontier AI models handle real finance work: valuation and modeling, credit analysis, investment memos,budgeting and variance analysis, treasury and risk decisions.
• You bring the judgment you have built sending analyst notes back for buried assumptions, defending a model to an investment committee, or explaining a variance to a CFO. We bring the model output that judgment is needed to grade.
• In this role, you will design challenging, realistic tasks drawn from your own practice, such as a three statement or DCF model with a valuation summary, a credit memo and covenant analysis, an investment committee memo, a budget versus actual variance analysis, a hedging or liquidity proposal, or a portfolio attribution, run them through frontier AI agents, and evaluate what comes back against a professional standard.
• You will work with realistic professional files, the kind a practitioner in your field actually handles, which you assemble yourself. Some tasks are compact, built around a handful of files; others are larger scenarios that take several days to build. In every case the goal is the same: a task a competent professional in your field would complete correctly and a frontier model currently gets wrong.
• Design challenging, realistic finance tasks drawn from your own day to day work: the scenario, a prompt phrased the way you would brief a trusted colleague, and the supporting files a professional would need (financial statements, models, data extracts, term sheets, board or IC materials, correspondence), which you author yourself.
• Compare two model outputs on identical prompts and files, decide which performed better, and document where each fell short.
• Write detailed grading rubrics that specify what a correct deliverable must contain, such as the right assumptions stated, the right calculations, the right risks flagged and the right recommendation, and explain in writing why a response passes or fails each one.
• Flag concrete failures with evidence: broken model logic, unsupported assumptions, misread financials, fabricated or ignored source files, unit and scaling errors, missed risks,and off brief interpretation of the ask.
• Contribute across valuation and modeling, credit, FP&A, markets, treasury and risk, and review and refine tasks built by other experts.

Qualifications

• Hands on experience preferred in corporate or investment finance.
• In progress Bachelor’s degree or higher in finance, economics, business or a quantitative field. CFA, FRM or securities licenses welcome but not required.
• Depth in at least one of: equity or fixed income research; portfolio management or trading; corporate finance and FP&A; credit analysis and underwriting; investment banking, M&A or corporate development; treasury and liquidity; market, credit or liquidity risk; wealth management; insurance, actuarial or underwriting.
• Builds and audits models at a practitioner level: three statement, DCF, comps, credit or budget models, not only consumes their outputs.
• CFA, CPA, FRM or securities licenses are welcome but not required and not screened for. Practical expertise outweighs credentials.

General requirements:

• General familiarity with AI and LLM tools. You have used models like Claude or ChatGPT in professional work and have the judgment to tell a well reasoned answer from a plausible sounding but incorrect one.

Process:

Assessment- 2-3 hours (unpaid)

There is no Interview- you muct complete and pass an assesment to gain access to the project