Quantitative Solutions – Liberty Mutual Investments
$100,000–$215,000 year
On-siteNew York City, New York, United States or Boston, Massachusetts, United States
Job Summary
Develop and maintain quantitative models and analytical tools that support asset allocation and portfolio construction decisions under insurance, regulatory, and rating agency constraints. Produce scenario analysis, stress testing, and portfolio analytics to inform long-term, annual, and tactical allocation decisions across public and private asset classes. Contribute to enhancements of models for private equity, private credit, real assets, and infrastructure while building data pipelines to source and integrate information from providers like PitchBook and Preqin. Support the development of commitment pacing, cash flows, and NAV forecasting models that integrate private markets into total portfolio construction. Partner with Investment Business Units to institutionalize analytics and contribute to cross-team research projects. This research-oriented role bridges the analytical gap between top-down asset allocation and bottom-up mandate execution within Liberty Mutual Investments' Global Strategy & Capital Allocation team.
Required Qualifications
- Master's degree in Financial Engineering, Statistics, Mathematics, Economics, Operations Research, or a related field
- 2+ years of experience in a quantitative research or related role
- Working knowledge of fixed income assets, public equities, and private markets
- exposure to private asset classes such as private credit, real assets, infrastructure, or private equity
- Strong applied quantitative skills, including experience with simulation techniques, statistical modeling, time series analysis, and optimization
- ability to build and maintain production-ready research tools
- Demonstrated knowledge of private asset classes, including private equity, private credit, real assets, or infrastructure
- understanding of fund structures, cash flow mechanics, performance metrics (IRR, MOIC, DPI, TVPI), and the challenges of working with private markets data
- Understanding of how private assets integrate into a total portfolio context, including the interplay between illiquidity, commitment pacing, vintage diversification, and portfolio-level risk and return
- Advanced programming and data skills in Python and SQL
- experience using version control (Git)
- comfort working with large, messy, and non-standardized datasets typical of private markets
Desired Qualifications
- experience using PitchBook, Preqin, Burgiss, and internal systems
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