About the role
Job Title: Private Equity Financial Modeler (Excel)
Location: Remote
Job Type: Contract Full Time; highly qualified candidates may be considered for Part time roles)
About the Opportunity
We are partnering with a venture-backed artificial intelligence company based in San Francisco that is building frontier AI systems for institutional financial reasoning.
Rather than running pre-built templates or summary dashboards, the platform is training AI models to think through investments the way institutional Private Equity professionals do: understanding how a deal is structured, how assumptions are stressed, and how valuation decisions are justified.
In this role, you will act as a core Private Equity subject-matter expert. You will build, audit, and benchmark institutional-grade buyout models entirely from a blank spreadsheet in Excel. Your completed models, formulas, and written step-by-step logic will serve as the ground-truth benchmark datasets used to train, test, and fine-tune AI models against Wall Street standards.
Key Responsibilities
- Blank-Sheet PE Modeling: Build dynamic, fully integrated LBO and operating models from a blank workbook in Excel without using templates, macros, plug-ins, or AI tools.
- End-to-End Deal Structuring: Construct every layer of a buyout model: purchase price adjustments, transaction fees, Sources & Uses, dynamic working capital schedules, multi-tier debt amortizations, and exit returns (IRR and MOIC).
- GP / LP Distribution Waterfalls: Design from-scratch equity distribution waterfalls incorporating hurdle rates,catch-ups, carried interest, and sponsor promotes across multiple investor classes.
- Deal Diligence Integration: Translate real-world Quality of Earnings (QoE) findings, normalized working capital pegs, and management adjustments into forward-looking balance sheet and cash flow drivers.
- Stress-Testing & Scenarios: Run multi-variable sensitivity tables and scenario analyses (base, downside, stress) evaluating debt paydown capacity, covenants, and returns across exit multiples and hold periods.
- Ground-Truth Logic Articulation: Document the explicit financial and accounting rationale behind modeling choices, step-by-step formulas, and deal mechanics in clear, structured English.
Must-Have Requirements
- 2–8+ years of direct experience in Private Equity, Buy-Side M&A Advisory, Search Funds, or Investment Banking (M&A / Leveraged Buyouts).
- True "From-Scratch" Excel Capability: Proven ability to structure, format, and build an institutional-grade LBO model from a blank sheet using strict keyboard-driven modeling hygiene (transparent formulas, zero circularity errors).
- Comprehensive LBO Mastery: Deep hands-on experience structuring Sources & Uses, purchase price allocations,debt sweeps, cash flow waterfalls, and investor returns under various exit horizons.
- Rigorous Accounting Foundation: Exceptional command of 3-statement financial accounting (US GAAP / IFRS),with specific experience handling QoE adjustments, EBITDA normalizations, and balance sheet flow-throughs.
- Full-Time Dedication: Availability to commit 35–40 dedicated hours per week on an ongoing basis.
- Written Communication: Fluent professional English with the ability to write clear, structured explanations of complex sponsor mechanics and accounting logic.
Nice-to-Have Qualifications
- Experience modeling add-on acquisitions and buy-and-build / roll-up strategies (pro forma platform plus add-on combinations).
- Experience with carve-outs, standalone pro forma adjustments, or transition service agreements (TSAs).
- Formal training from an investment bank or private equity analyst training program.
- Progress toward or completion of the CFA charter.
Why Join?
- Shape AI Financial Reasoning: Directly train frontier AI systems on complex, institutional private equity logic.
- Full Autonomy: 100% remote and fully asynchronous—manage your own working hours around deliverable milestones.
- Competitive Global Pay: Reliable monthly contractor compensation aligned directly with your technical modeling depth and weekly output.