Data Scientist

Who We Are BH Management, LLC is a people-first multifamily owner and operator that grew from a small startup into one of the nation's largest commercial real estate companies. Founded in 1993, BH is celebrated for its simple commitment to doing business the right way and investing in its team. Today, BH manages over 100,000 units, employs over 2,800 people, owns its processes in-house, and is praised by Fortune Magazine as the “Best Workplace for Women,” “Best Workplace for Millennials,” and “Best Workplaces for Diversity.” Powered by innovation and a can-do attitude, BH improves daily, striving to construct a smarter way to live, invest, manage, and grow. BH is passionate about setting the standard in the multifamily industry. We are a welcoming band of go-getters who think big, sweat the details, and take our work (but never ourselves) too seriously. We set our sights high, own our mistakes, and turn lemons into lemonade. We are incredibly proud of where we’ve come and are ready to tackle what’s next. Come join us! Job Functions: Develop, validate, and optimize machine learning models based on defined business and technical requirements, including target variable design, feature engineering, data partitioning strategies, and evaluation of candidate algorithms such as regression, logistic regression, LightGBM, XGBoost, CatBoost, and hybrid forecasting architectures. Create and maintain features, labels, and analytical datasets from core business data sources, including unit status history, application and leasing workflows, renewal activity, and resident experience and sentiment data. Generate model explainability and interpretability outputs that enable stakeholders to understand, trust, and confidently act on model-driven insights and recommendations. Monitor production model performance through ongoing validation, drift detection, and error tracking processes, including Population Stability Index (PSI) analysis and identification of retraining opportunities when model performance degrades. Conduct model governance and compliance reviews by validating adherence to Fair Housing and other applicable regulatory requirements, including testing for disparate impact and ensuring protected-class attributes are excluded from model development and scoring processes. Document model methodologies, assumptions, decisions, limitations, and data-quality considerations through code, configuration files, technical documentation, and audience-appropriate summaries for both technical and business stakeholders. Partner with Revenue Management, Leasing Operations, Resident Experience, and other cross-functional teams to deliver ad hoc analyses, actionable insights, and data-driven recommendations that support strategic and operational decision-making. Other duties as assigned Minimum Qualifications/Skills: 2+ years of experience in data science, applied machine learning, quantitative analytics, or a related field. Experience in multifamily housing, real estate, or property management is beneficial but not required. Demonstrated proficiency in Python (including libraries such as pandas, NumPy, and scikit-learn) and SQL, with experience querying and integrating data across multiple sources, performing complex joins, and ensuring data accuracy in analytical calculations and reporting. Experience developing and evaluating machine learning models using at least one gradient-boosting or ensemble framework, such as LightGBM, XGBoost, or CatBoost, with knowledge of classification, forecasting, or time-series modeling techniques. Understanding of foundational data science and machine learning principles, including data partitioning strategies, prevention of data leakage, class imbalance management, model validation, and explainability approaches such as feature importance analysis and SHAP. Ability to work with feature engineering datasets, target variable definitions, business requirements, and model evaluation criteria throughout the model development lifecycle. Working knowledge of relational databases, data modeling, and data warehousing concepts. Experience with platforms such as SQL Server, Snowflake, or similar enterprise data environments is preferred. Strong analytical, problem-solving, and attention-to-detail skills, with the ability to communicate technical concepts, model outputs, and insights clearly to both technical and non-technical audiences. Ability to manage multiple priorities in a fast-paced environment while maintaining high standards for accuracy, documentation, and data quality. Exposure to advanced analytical and machine learning methodologies, including causal inference techniques (such as difference-in-differences, synthetic control, and double machine learning), survival analysis, hierarchical or multi-level forecasting approaches, and model reconciliation methods. Familiarity with Jupyter-based machine learning workflows, experiment tracking, and reproducible research and development practices is also preferred. Competencies: Core – Proficiency Level: 1 Communication Customer Focus Teamwork and Collaboration Embrace Evolution Inclusion Functional – Proficiency Level: 1 Strategic Judgement Change Management Execution Ownership Professional Presence Influence Business Acumen Work Schedule: Monday-Friday (work schedule may vary). Some overtime may be required and ability to work extended hours as needed to meet business needs. Physical Requirements/Environment: The physical requirements described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. This job generally operates in a professional office environment but may also occasionally operate in an outdoor environment. While performing the duties of this job, employees must be able to remain in a stationary position for extended periods, occasionally moves throughout the office, constantly operates a computer and other office equipment, frequent and repetitive motion, including movements of the wrists, hands and/or fingers, communicate regularly and effectively with others, both written and verbally, and may occasionally lift up to 30 pounds. This position requires close visual acuity to perform an activity such as preparing and analyzing data and figures, viewing a computer terminal, and extensive reading. The ability and means to travel locally, overnight, in specific regions or states via automobile and airplane may be required. BH is an Equal Employment Opportunity Employer. We foster the diverse voices of our community by advocating for inclusivity, celebrating our differences, and continually evolving our practice to make BH a better place to work and live. Our posted compensation reflects the cost of talent across multiple US geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience.