Financial Modeler

We are partnering with a U.S.-based technology company building advanced AI systems focused on financial modeling and decision-making.

The goal is to train AI to think like real financial professionals — how models are built from scratch, how assumptions are structured, and how decisions are made using financial models.

This is a hands-on Excel modeling role. You will be expected to build detailed financial models from a blank spreadsheet and clearly explain your logic.

We prioritize strong model builders over specific domain experience. Candidates from investment banking, private equity, credit, or corporate finance are encouraged to apply if they have built full models from scratch.

• 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

• 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

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.

You must have deep, hands-on experience building full financial models from scratch in at least one of the following areas. We value strong model builders who can adapt across domains.

(1) 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

(2) Private Equity (LBO Modeling)

• Full LBO models built from scratch

• Sources & uses, debt schedules, returns (IRR/MOIC)

• Operating models with sensitivities and exit scenarios

(3) Asset-Based Lending (ABL) (optional / less common)

• Borrowing base models (AR, inventory)

• Advance rates, eligibility, dilution

• Collateral-driven lending structures

(4) Structured Finance / Asset-Backed Securities (ABS) (optional / less common)

• Cash flow waterfall models

• Tranching, credit enhancement, loss assumptions

• Prepayment/default scenario modeling

(5) Risk & Portfolio Modeling

• Scenario and stress-testing models

• Loss modeling (default, recovery, exposure)

• Portfolio-level analysis driven by model outputs

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

• 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)

Your experience is primarily:

• Reviewing modes, 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

• 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

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.