$80–100/hr
The role in one line
Build real estate transaction models from source documents and review peer models against established quality standards.
Written by Training Turk from the public listing; it may be incomplete or out of date. Read the full posting on Mercor.
What you would do
- Construct Excel financial models from complete deal document packages using formulas and assumptions without templates
- Deliver workbooks with live formulas, proper sourcing of inputs, and documented assumptions
- Review two peer-built models against fixed scoring criteria with written assessment
- Provide rationale and completed scorecards for each model peer review
- Analyze deal structure and validate modeling approaches for consistency and correctness
Who they are looking for
- 2-4 years total experience including approximately 2 years investment banking in real estate or industrials
- Currently or recently served as Associate at a mid-market or upper-mid-market real estate focused PE fund
- Demonstrated ability to build financial models from source documents without relying on templates
- Fluent English for clear communication and written documentation
- Available for approximately 20-25 hours of work over 1.5-2 weeks
Skills this role asks for
What the interview is likely to probe
1.Model Structure from Raw Documents
Building models without templates requires judgment about which assumptions drive returns and how to structure logic; this reflects true analytic capability.
Expect something like: “You receive 50 pages of property documents, financing terms, and market data with no existing model template. How would you organize your workbook tabs and define your key assumptions?”
2.Real Estate Valuation Methodology
Peer review requires understanding whether an analyst chose appropriate valuation methods and reasonable assumptions for different property types and markets.
Expect something like: “You review a model that uses straight-line rent escalation for a net-lease investment. When would you flag this assumption as problematic versus defensible?”
3.Identifying Modeling Errors in Peer Work
Spotting mistakes in formulas, circular references, and logical inconsistencies distinguishes strong analysts; this judgment is rare and valuable in training data.
Expect something like: “A peer's model shows debt balance increasing in year 3 despite stated amortization schedule. How would you investigate this discrepancy and determine if it reflects an error or intentional structure?”
4.Deal Assumption Quality Assessment
Evaluating whether assumptions reflect market reality versus analyst overoptimism requires practical deal experience and scrutiny of comps, cap rates, and rent growth.
Expect something like: “The model assumes 4% annual rent growth but provides no market data supporting that projection. How would you assess whether this assumption is reasonable for the property type and location?”
5.Financial Logic and Deal Structure Understanding
Understanding how leverage, timing, and exit assumptions interact in returns requires both technical Excel skill and genuine deal judgment that can be trained into models.
Expect something like: “Model A and Model B produce the same exit return but different interim cash flows. What details would you examine to determine which modeling approach more accurately captures deal economics?”
Exercise you may get
Build a model from a real estate deal document set, then review a peer model against scoring criteria with written rationale.
How to prepare
- Review real estate deal structures and typical assumptions in middle-market private equity transactions
- Refresh Excel skills including formula construction, error-checking, and sensitivity analysis techniques
- Study common mistakes in real estate models including circular references and assumption mismatches
- Practice explaining financial modeling choices in writing with clear, structured rationale
Facts
- Pay
- $80–100/hr
- Commitment
- hourly
- Work arrangement
- remote · United States (remote)
- Eligible locations
- USA
- Domain
- Finance
- Company
- Pearson
- Posted
- 9/17/2026
- Open slots
- 3