Lead Data Scientist

Join the elite Data Science squad of a
leading global private equity firm specializing in real assets
. This is a high-impact, senior-level role where you will design and deploy
trusted forecasting models and advanced valuation tools
across one of the world's largest real estate portfolios. Your work will directly influence multi-billion dollar investment decisions, underwriting assumptions, and portfolio optimization strategies.

We are seeking a highly capable practitioner who combines
strong quantitative modeling skills
with a solid understanding of
real estate fundamentals and investment buy-side logic
to partner directly with executive investment teams and define the future of data science at the firm.

What You Will Do:

• Strategic Modeling:
  Architect, build, and deploy trusted forecasting, valuation, and performance models across diverse asset classes.
• Investment Partnership:
  Work directly with Investment, Asset Management, and Capital Markets teams to convert complex buy-side questions and risk scenarios into robust, analytical workflows.
• Data Integrity:
  Take ownership of data quality, reconciling noisy or fragmented operational and financial datasets, and collaborating with data engineers (Snowflake/DBT team) to ensure data is model-ready.
• Leadership & Standards:
  Establish best practices for model validation, documentation, and monitoring, setting the bar for data science excellence within the firm.
• Mentorship:
  Serve as the senior technical practitioner, providing mentorship and guidance to analysts and junior data scientists.

Required Qualifications:

• 6+ years in applied data science, quantitative analytics, or modeling roles.
• Direct experience in one or more of the following areas:
  Commercial Real Estate (CRE), Real Estate Private Equity, Institutional Real Estate Investing,
  or
  Real Estate Analytics.
• Modeling Proficiency:
  Hands-on experience building models specifically for investment decisions, predictive forecasting, or underwriting (e.g., AVMs, time-series, risk scenarios).
• Communication:
  Exceptional ability to partner with and clearly explain complex model results, assumptions, and risks to non-technical executive and investment audiences.
• Education:
  Bachelor's or Master's degree in a quantitative field (Statistics, Economics, Applied Math, etc.) or equivalent professional experience.

If you are ready to drive investment outcomes in the world of real assets, seize this unique opportunity and
apply today
to start a discussion with our team.