Note: The job is a remote job and is open to candidates in USA. John Burns Research and Consulting is an independent research and consulting firm serving the housing industry through forecasts, indices, and analysis. The Senior Data Scientist will build and maintain forecasting models and housing indices, improve modeling methodologies and quality assurance, and partner with economists, researchers, and engineering teams to productionize and communicate model results.
Responsibilities
- Build, validate, and maintain time-series and econometric forecasting models across multiple horizons, including backtest design, out-of-sample validation, and model diagnostics
- Advance the methodology behind JBREC's published forecasts and indices as data sources, techniques, and best practices evolve
- Develop and extend forecast quality assurance and anomaly detection across our production models
- Specify and build the calculations behind published JBREC metrics within our governed semantic layer, in partnership with data engineering
- Conduct feature engineering and evaluation against our licensed data assets, with clear evidence of whether a change measurably improves forecast performance
- Partner with our economists and researchers to brainstorm, test, build, and refine new forecasting models
- Document model logic to a standard where a colleague can reproduce a result independently
- Contribute to the team's technical practices through code review, pairing, and shared tooling
- Partner with data engineering and software engineering to bring models into production and keep them performing well over time
- Explain methods and results clearly to economists, research leadership, and consulting teams
Skills
- 5+ years building and validating forecasting, econometric, or predictive models on large, complex datasets in a research or applied analytics setting
- Real depth in time-series methods. You can speak to backtest design, guarding against leakage, and why you chose a given specification
- Strong Python and SQL. R welcome in addition
- Experience working in version-controlled, reproducible environments: git, code review, and documented pipelines. You treat a model as code rather than as a notebook
- Experience maintaining models after they ship, including monitoring, diagnosing drift, and deciding when to retrain or rebuild
- Sound judgment about model selection, and the ability to explain in plain language why one approach was chosen over another
- Bachelor's degree in data science, mathematics, statistics, computer science, finance, economics, or another quantitative discipline, or equivalent applied experience
- Clear written and verbal communication, including documentation that colleagues rely on
- We cannot hire anyone who currently requires or will in the future require sponsorship to work in the United States
- Housing, real estate, mortgage, construction, or macroeconomic forecasting experience
- Experience working in a modern cloud data platform environment
- Familiarity with public data sources used in housing research, such as Census ACS and PUMS, BLS series, HMDA, and county assessor or parcel data
- Experience contributing to a published index, benchmark, or recurring forecast product
- Experience mentoring analysts or strengthening technical practices on a team
- Experience with dbt, or an equivalent framework for governed transformations and centralized metric definitions
Benefits
- $12,500 towards comprehensive benefits, including medical, dental, vision, prescription drug coverage, and flexible spending accounts including gym memberships and vacation assistance.
- Company contributes 5% of their salary and profit sharing to their 401(k), even if they do not contribute.
- 30 days of Paid Time Off including 3 weeks of personal time off (PTO), 10 paid holidays, and 5 paid days for our Winter Break when the company shuts down to rejuvenate.
Company Overview