Valuation Science
Valuation Data Scientist
Turn commercial real estate transactions into valuation evidence a hearing officer can follow. You will extract market cap rates, build adjustment methods that can be defended line by line, and measure assessment equity with ratio study statistics.
What you will do
- Extract cap rates, rents, vacancy and expense benchmarks from verified arms-length sales and submarket data.
- Develop sales comparison adjustments for size, age, condition, location, parking ratio and market conditions, using paired sales and regression with transparent coefficients.
- Compute ratio study statistics, including median ratio, coefficient of dispersion and price-related differential, to support uniformity analysis.
- Validate the Income Valuation engine's normalization, loaded cap rates and reserves against accepted appraisal practice.
- Write plain-language method notes so that every number in an evidence packet can be explained to an assessor or board member.
- Work with the Head of Valuation Science to retire any method that cannot be explained.
What you bring
- 4 or more years in data science, quantitative research or econometrics.
- Strong Python and SQL, and a command of regression, sampling and uncertainty.
- A preference for models you can explain over models that score slightly better.
- Interest in real estate valuation and the discipline to learn appraisal vocabulary and methods.
Nice to have
- A CFA charter, or progress toward an MAI, CCIM or similar designation.
- Experience at an appraisal firm, an assessor's office or a commercial real estate research team.
- Familiarity with CoStar, ATTOM or other commercial property data.
- Experience writing for non-technical readers.