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Global Asset Manager is in search of a Quantitative Investment Analyst supporting its multi-asset portfolio solutions platform. In this role, you will develop and implement advanced portfolio optimization frameworks to enhance private market portfolios, considering complexities such as illiquidity, capital calls, distributions, and sector/geographic constraints. Your work will include building and refining quantitative models for expected returns, risk, cash flow forecasting, and correlations, enabling smarter decision-making. You will leverage data from leading providers and internal sources to conduct insightful research, contribute to risk measurement innovations, and support the creation of thought leadership on private portfolio construction and risk management.
Responsibilities: Design and implement portfolio optimization tools across multiple asset classes. Develop models that incorporate illiquidity, capital flow timing, and leverage. Build simulation engines (Monte Carlo, scenario analysis) to evaluate portfolio outcomes. Work closely with portfolio managers, analysts, and risk teams to deliver actionable insights. Contribute to whitepapers on private market risk, construction, and design.
Qualifications
Must-Have Skills & Qualifications:
  • Bachelor’s or Master’s degree in Mathematics, Statistics, Physics, Computer Science, or a similarly quantitative field. 4+ years of experience in private markets investment, pension funds, sovereign funds, or asset management
  • Strong understanding of private market cash flow dynamics—capital calls, distributions, NAV.
  • Proficiency in SQL and Python, with experience in portfolio optimization software (e.g., Gurobi, Mosek).
  • Familiarity with factor models and risk management tools (Bloomberg, Barra, Axioma).
  • Experience working with large datasets and data visualization tools (Tableau, R, Python).

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Level

Senior L5

Location

Glens Falls, NY

Occupation

Financial Quantitative Analysts

Industry

Portfolio Management and Investment Advice

Posted

3 days ago

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