Senior Data Scientist

We are hiring a Senior Data Scientist to join the team behind JBREC’s forecasting models and proprietary housing indices. This is a hands-on senior individual contributor role for someone who wants their modeling work used, cited, and acted on across the industry.

You will work alongside housing economists and researchers who know this market as well as anyone in the industry, and alongside data and software engineers building the platform underneath it. We are investing heavily in that platform right now, including a governed semantic layer so that every published number traces cleanly back to a definition someone owns. You would be building on that foundation rather than working around it.

Our data science function is growing. This seat carries real scope from day one and is positioned to take on more as the team expands.

Reporting Structure

This position sits within the technology group and reports to the Senior Manager, Data Science. It works closely with our economists, research directors, data engineering, software engineering, and consulting teams., * 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.

• 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.

Preferred Qualifications

• 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.

What Makes You Successful Here

• You care about whether the model is right, not whether it is impressive.
• You take ownership and move work forward without waiting to be asked.
• You hold a high bar for accuracy and you speak up when something does not look right.
• You make the people around you better at the technical craft.
• You use AI as a tool for learning and getting things done, not as a substitute for understanding.
• You are curious about housing and want to understand the market, not just the data.
• You are organized and adaptable, and you work well against a research calendar that does not wait.
• You are able to communicate and articulate complex concepts clearly to a variety of audiences.

$12,500 towards our 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.

Compensation and title will be based on skills, experience, and abilities, which can vary by person.