Residential Real Estate Investment Analyst – Underwriting & Proformas (Advanced Google Sheets)

Remote, USA Full-time
Overview We are seeking an experienced Residential Real Estate Investment Analyst to support underwriting and financial modeling for residential acquisitions and development/reposition projects. The primary deliverable is clean, decision-grade proformas and dynamic financial models built in Google Sheets (preferred) that we can use for repeatable deal analysis, scenario testing, and stakeholder reporting. This role is ideal for someone who is highly analytical, detail-oriented, and fluent in building scalable, auditable Google Sheets models. Key Responsibilities Build and/or refine residential real estate underwriting models and proformas in Google Sheets. Create structured, easy-to-audit models with clear assumptions and outputs. Analyze acquisition, rehab/value-add, BRRRR-style, and build/sell or build/rent scenarios. Build financing modules (debt schedules, interest-only periods, amortization, refinance, balloon, prepay, etc.). Create sensitivity and scenario analysis (rent growth, cap rates, exit price, rehab budget, vacancy, interest rates). Calculate and present key investment metrics: IRR, MOIC/equity multiple, cash-on-cash, NOI, DSCR, debt yield, breakeven occupancy, stabilized yield. Provide concise investment summaries that explain key assumptions, risks, and conclusions. Implement QC checks (balance tests, flags, consistency checks) to ensure reliability and prevent formula errors. Required Skills & Experience Proven experience underwriting residential real estate (SFR, small multifamily, value-add/rehab, portfolios, and/or ground-up). Advanced Google Sheets skills (required): Array formulas / structured formula design Named ranges / data validation Query(), Filter(), Index/Match/Xlookup equivalents Scenario modeling and sensitivity tables Clean model architecture (inputs → calculations → outputs) Auditable formatting and error-proofing Strong grasp of real estate finance and valuation: NOI, cap rates, rent/expense assumptions, capex planning, debt structuring, exit underwriting. High attention to detail and a “tie-out” mindset—models must reconcile correctly and be easy to review. Clear communication and ability to document assumptions. Software & Tools Preferred / Required: Google Sheets (advanced) – REQUIRED Google Drive collaboration workflows (permissions, versioning, comments) Nice to Have: Microsoft Excel (secondary) Power BI / Looker Studio dashboards AppScript automation (Google Sheets) Python (for bulk analysis or data cleanup) Familiarity with comp tools (MLS exports, CoStar, Rentometer, AirDNA for STR, etc.) Deliverables Expected A reusable Google Sheets underwriting template (or improvements to our existing model) including: Assumptions / Inputs tab (clearly labeled, validated) Cash flow tab (monthly or annual as appropriate) Debt / financing schedule tab (with refi scenarios) Returns & metrics tab (IRR, CoC, equity multiple, etc.) Sensitivity / scenarios tab Optional: clean dashboard summary for quick decisioning One completed underwriting per deal using provided inputs and comps (trial phase). Project Type Start with 1–3 deals as a paid test projects. Strong performance can lead to ongoing work (deal-by-deal underwriting support). Time Commitment & Turnaround Remote, flexible. Typical turnaround expected: 24–72 hours per deal once inputs are provided (depending on complexity). To Apply (Please Include) Brief overview of your residential underwriting experience (asset types, deal sizes, strategies). A sample Google Sheets model you built (redacted is fine) or screenshots showing structure and outputs. Your approach to model structure and QC (how you prevent errors and ensure auditability). Your hourly rate and/or fixed-fee estimate for a standard underwriting model in Google Sheets. Bonus Points You’ve modeled For Sale Subdivisions, BRRRR, value-add rehabs, construction-to-perm, and/or build-to-rent. You can produce a one-page “IC-style” investment summary with clear assumptions and decision points. You can automate repetitive tasks with AppScript. Apply tot his job
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