Director, Investment Research

Brookfield Asset Management•Charleston, SC

23h•Onsite

About The Position

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. This role defines the requirements for those tools and partners with data science and engineering colleagues to bring them to life. The role will partner closely with Investments, Asset Management, Finance, Revenue Management, and Executive Leadership, in particular the CEO and CIO of Maymont. The ideal candidate combines strong quantitative and research capability with financial and strategic thinking. This individual is equally comfortable making sense of complex and ambiguous data, analyzing investment opportunities, evaluating housing markets, applying mid-level econometrics, and presenting crisp analytical insights to executive leadership. They are technically fluent enough to collaborate credibly with data science and engineering teams and to program-manage analytical work without needing to serve as the engineering lead. Success in this role requires curiosity, business acumen, and the ability to transform complex data into actionable investment recommendations. More specifically, the candidate has the intellectual range to receive a thesis-level research question, such as “where should we be investing given the silver tsunami demographic shift?” and return within roughly two weeks with substantial progress on that question, potentially a geospatial analysis, an emerging investment thesis, and/or a recommended MVP approach, delivered as a decision-ready briefing. Once the approach is reviewed and approved by leadership, this person would advance it further by prototyping in AI-assisted tools such as Claude Code and then scope and build alongside our data science and engineering teams.

Requirements

Bachelor's or master's degree in Data Science, Statistics, Economics, Finance, Applied Mathematics, Computer Science, Engineering, or a related quantitative field.
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).
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.
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.
Experience evaluating investment opportunities through quantitative analysis, financial modeling, forecasting, scenario analysis, and portfolio performance measurement.
Experience analyzing housing markets, rental pricing, acquisition underwriting, portfolio optimization, demographic trends, geospatial data, competitive intelligence, and macroeconomic indicators affecting residential real estate investments.
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.
Experience leveraging Generative AI and modern AI tools to accelerate research, generate market intelligence, and improve analytical efficiency.
Ability to frame ambiguous business problems, develop analytical approaches, and translate findings into strategic recommendations.
Ability to distill complex analysis into succinct, decision-ready briefings and slides for technical and non-technical audiences, including executive leadership.

Nice To Haves

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.
Experience utilizing geospatial analytics and external market data sources.
Familiarity with modern AI platforms and cloud-based analytics environments.

Responsibilities

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