Director, Investment Research

Position Summary

The Director of Investment Research is responsible for independently scoping, executing, and delivering investment-grade research that translates complex demographic, macroeconomic, and market data into specific, actionable capital deployment opportunities. This research forms the foundation for the analytics and decision-support tools that enable the organization to make faster, smarter, and more informed decisions, primarily supporting investment decisions but also operational workflows.

Essential Job Functions

• Own a self-managed research roadmap driven by senior executive priorities, conducting independent deep-dive research sprints (typically 1-3 weeks) that deliver investment-grade analysis spanning full U.S. Housing platform: single-family rental, build-to-rent, senior housing, affordable housing, manufactured housing, and market-rate multifamily.
• Define the requirements for dynamic tools within our proprietary analytics application, for example, specifying how a geospatial demographic analysis should become an interactive heat map that enables platform-level investment decisions, and partner with the data science and engineering teams that build them.
• Set the standard for what good looks like and program-manage the effort to delivery.
• Build working MVPs and prototypes—leveraging AI-assisted development tools such as Claude Code and working proficiency in Python—that validate an approach and can be handed off to the engineering team to harden and productionize.
• Analyze housing market trends, demographic shifts, competitive positioning, and macroeconomic factors impacting investment performance.
• Respond to ad hoc analytical requests from leadership with fast, rigorous turnarounds. For example, identifying markets / areas that should out-perform by identifying demographic shifts to product types, and then packaging the findings into succinct, actionable, decision-ready output.
• Translate complex analytical findings into concise recommendations for executive leadership and investment teams.
• Partner with Data Engineering to ensure the analytical datasets the role relies on are reliable and trusted.
• Evaluate emerging techniques and external data sources to continuously improve the organization's analytical capabilities and the quality of its investment research.
• Perform other duties as assigned to support business objectives.

Performance Expectations & Key Metrics

• Decision Support: Develop analytical frameworks that improve market analysis, portfolio optimization, and overall investment performance.
• Strategic Analysis: Identify emerging opportunities and risks through advanced analytics, econometrics, and quantitative research.
• Research Impact: Deliver platform-spanning investment research that directly informs capital deployment decisions measured by speed of thesis-to-recommendation cycle (target: 2 weeks for a defined research question), quality of cross-platform opportunity identification, and the degree to which research outputs inform funded investments and approved decisions.
• Analytical Innovation: Leverage AI and emerging tools to accelerate research, sharpen analytical rigor, and improve organizational efficiency.
• Data Quality & Analytical Standards: Ensure analytical rigor, statistical integrity, reproducibility, and documentation across all research and analyses.

Required Qualifications

• Education: Bachelor's or master's degree in Data Science, Statistics, Economics, Finance, Applied Mathematics, Computer Science, Engineering, or a related quantitative field.
• Experience: Minimum of 6-8 years of experience in quantitative research, investment analytics, or applied economic/market analysis, with demonstrated investment-side experience (investment committee exposure, memo writing, or capital deployment decisions preferred).

Skills & Competencies

• Strong problem-solving skills and attention to detail.
• Demonstrated ability to influence strategic business decisions through analytical insights.
• Excellent communication, collaboration, and presentation skills with both technical and executive stakeholders.
• Quantitative & Statistical Analysis: Strong command of statistical modeling, econometrics, forecasting, regression, clustering, and predictive analytics, with a working understanding of the model development lifecycle sufficient to scope and evaluate the work of technical teams.
• Investment & Financial Analysis: Experience evaluating investment opportunities through quantitative analysis, financial modeling, forecasting, scenario analysis, and portfolio performance measurement.
• Real Estate Analytics: Experience analyzing housing markets, rental pricing, acquisition underwriting, portfolio optimization, demographic trends, geospatial data, competitive intelligence, and macroeconomic indicators affecting residential real estate investments.
• Data Fluency: Working proficiency in SQL and Python for data analysis (e.g., pandas), sufficient to independently explore data and analyses and to communicate precisely with the data science and engineering teams.
• Artificial Intelligence: Experience leveraging Generative AI and modern AI tools to accelerate research, generate market intelligence, and improve analytical efficiency.
• Strategic Thinking: Ability to frame ambiguous business problems, develop analytical approaches, and translate findings into strategic recommendations.
• Communication: Ability to distill complex analysis into succinct, decision-ready briefings and slides for technical and non-technical audiences, including executive leadership.

Preferred Qualifications

• Master's degree or PhD in Data Science, Statistics, Economics, Finance, Operations Research, or MBA with a quantitative focus.
• Experience within real estate, private equity, investment management, asset management, or financial services.
• Experience developing predictive pricing, forecasting, or optimization analyses, and working with technical teams to put them to use.
• Familiarity with modern AI platforms and cloud-based analytics environments.