About the Role
This role involves hands-on financial modeling in Excel to train AI systems in professional financial reasoning. Candidates should be able to construct models independently, explain their logic clearly, and demonstrate experience in building full models from blank spreadsheets. Domain expertise is less important than strong modeling fundamentals.
Responsibilities
- Construct financial models from the ground up in Excel for various financial scenarios
- Examine and troubleshoot models created by others
- Detect flawed assumptions, faulty logic, and potential risks in models
- Evaluate interconnections between cash flow, debt structures, and investment returns
- Articulate financial reasoning and decision logic clearly
- Convert practical financial analysis into structured, logical outputs
Work Arrangement
Remote (Worldwide)
Areas of Modeling Experience
- Credit & Lending Models - 3-statement borrower models - Cash flow-based lending and debt sizing - Covenant modeling (DSCR, leverage, coverage ratios) - Loan structuring and scenario analysis
- Private Equity (LBO Modeling) - Full LBO models built from scratch - Sources & uses, debt schedules, returns (IRR/MOIC) - Operating models with sensitivities and exit scenarios
- Asset-Based Lending (ABL) (optional / less common) - Borrowing base models (AR, inventory) - Advance rates, eligibility, dilution - Collateral-driven lending structures
- Structured Finance / Asset-Backed Securities (ABS) (optional / less common) - Cash flow waterfall models - Tranching, credit enhancement, loss assumptions - Prepayment/default scenario modeling
- Risk & Portfolio Modeling - Scenario and stress-testing models - Loss modeling (default, recovery, exposure) - Portfolio-level analysis driven by model outputs
What You’ll Do
- Build financial models from scratch in Excel across different use cases
- Review and debug models built by others
- Identify incorrect assumptions, broken logic, and risks
- Analyze relationships across cash flow, debt, and returns
- Clearly explain financial logic and decision-making
- Translate real-world financial thinking into structured outputs
What Makes a Strong Candidate
- 2–10 years of experience in finance roles with heavy modeling exposure
- Proven ability to build models from a blank spreadsheet (no templates)
- Experience building decision-driving models (not just outputs or summaries)
- Strong understanding of how models are used in real financial decisions
- High attention to detail and model accuracy
- Strong communication skills (English required)
Not a Fit If
- Your experience is primarily: - Reviewing models, making small updates, focused on pitch decks, comps, or outputs without building full models
- - FP&A reporting, budgeting, or dashboards
- - Credit review without hands-on model building
- - BI tools, analytics workflows, or reporting automation
- Or: - You have not built full financial models yourself
- - You rely heavily on templates, tools, or AI to generate models
- - You are not comfortable explaining your work in detail
Interview Process
- All candidates will complete a ~3-hour take-home Excel modeling exercise.
- Designed to reflect real-world modeling work
- Must be completed independently in Excel
- Candidates who are hired will be paid for this exercise
Final Note
Candidates from investment banking, private equity, debt, credit, corporate finance, treasury, quantitative finance, or related modeling-heavy backgrounds are encouraged to apply if they have built full financial models from scratch, regardless of your specific domain background.
Other
- 15–40 hours/week
- Flexible, asynchronous work
- English required
This role IS
- Building financial models from a blank spreadsheet
- Structuring assumptions, drivers, and logic
- Linking full model flows (cash flow, debt, returns, scenarios)
- Debugging and improving model accuracy
- Explaining why a model works, not just producing outputs
This role is NOT
- Dashboards, reporting, or data visualization
- Traditional FP&A roles focused primarily on reporting, budgeting, or dashboards without hands-on financial model building
- Reviewing credit without building models
- High-level strategy without hands-on modeling
- Using AI tools to generate models
What Good Looks Like
Strong candidates have built full financial models end-to-end (e.g., LBO, 3-statement, credit, or project finance models) and can clearly explain every component of the model.
