Data Scientist

About the role

TTwelve is seeking a Data Scientist to advance the analytical systems behind TTwelve Intelligence.

TTwelve evaluates multifamily property performance across reports, data sources, operating periods, markets, and management activity. The work requires more than building predictive models. It requires understanding imperfect real-world operating data, identifying meaningful relationships, testing competing explanations, and translating analysis into conclusions that can support real ownership decisions.

The Data Scientist will work closely with engineering, operations, and real estate subject-matter experts to develop analytical methods that are rigorous, explainable, and useful.

Responsibilities

• Develop analytical methods for evaluating multifamily property performance.
• Analyze relationships across rents, leasing, occupancy, collections, expenses, operating results, and management activity.
• Build methodologies for trend detection, anomaly detection, forecasting, benchmarking, and root-cause analysis.
• Work with proprietary multifamily performance data across more than 2,400 submarkets.
• Evaluate correlations, likely causal drivers, and alternative explanations for changes in property performance.
• Build and validate statistical models and analytical tools.
• Establish rigorous testing, validation, and monitoring methodologies.
• Work with engineering to translate analytical methods into reliable production systems.
• Develop performance benchmarks and comparative analytical frameworks.
• Document methodologies, assumptions, limitations, and validation results.
• Communicate analytical conclusions clearly to both technical and nontechnical audiences.

Qualifications

• Strong background in data science, statistics, econometrics, applied mathematics, economics, or a closely related discipline.
• Strong Python and SQL skills.
• Experience working with large, imperfect, heterogeneous, or longitudinal datasets.
• Strong understanding of statistical inference, regression, forecasting, experimental or quasi-experimental methods, and model validation.
• Ability to distinguish predictive relationships from causal claims.
• Strong analytical judgment and intellectual discipline.
• Ability to communicate complex analytical work clearly.
• High standards for reproducibility and data integrity.

Relevant experience

Experience with real estate, financial data, behavioral economics, econometrics, time-series analysis, causal inference, or operating-performance analytics is particularly relevant.

Success in this role

Success will be measured by analytical accuracy, quality of validation, improvement in TTwelve’s diagnostic and forecasting capabilities, usefulness of analytical findings, and the successful translation of research into production systems.

About TTwelve

TTwelve provides operating intelligence for multifamily ownership. We combine real estate operating knowledge, proprietary data, analytics, and technology to help owners understand where their properties are heading, identify issues earlier, and improve management accountability.

Working at TTwelve

TTwelve is based in Los Angeles and operates as a remote organization. We give people the flexibility to work where they are most effective while maintaining clear expectations around communication, accountability, and quality.

Benefits

TTwelve offers paid vacation and parental leave so employees have the time and flexibility to take care of themselves and their families. We believe strong performance should be recognized, with performance-based bonuses and a technology allowance to support effective work. Our benefits package also includes PPO medical coverage, along with dental and vision benefits.

What we value

We want smart, grounded people who take the work seriously without taking themselves too seriously. We value trust, candor, accountability, strong judgment, curiosity, and genuine respect for the people we work with.

Equal opportunity

TTwelve is an equal opportunity employer. Employment decisions are based on qualifications, merit, and business needs without regard to characteristics protected by applicable law.