Quantitative Solutions - Liberty Mutual Investments

Liberty Mutual; Boston (MA); On-site; USD 85,000 - 110,000; Full time

Job summary

Liberty Mutual in Boston seeks a Quantitative Solutions professional to develop and maintain analytical tools supporting asset allocation. The role covers developing models, conducting scenario analysis, and integrating private market data.

The ideal candidate holds a Master's degree in a related field and has at least 2 years of experience, with strong skills in Python and SQL. Liberty Mutual fosters an inclusive environment where diverse perspectives are valued.

Qualifications

• Minimum 2 years of experience in quantitative research or related role.
• Working knowledge of fixed income assets and public equities.
• Demonstrated knowledge of private asset classes.

Responsibilities

• Develop quantitative models and analytical tools.
• Produce scenario analysis and portfolio analytics.
• Support commitment pacing and cash flows modeling.

Skills

Quantitative modeling

Statistical analysis

Programming in Python

Data analysis in SQL

Simulation techniques

Education

Master's degree in Financial Engineering or related field

Tools

Git

Job description

Quantitative Solutions – Liberty Mutual Investments

Job Locations: US-MA-Boston | US-NY-New York

Liberty Mutual Investments (LMI) is an investment firm focused on fixed income, equity, and alternative strategies, investing over $100B globally. LMI seeks a highly motivated individual to contribute to the Quantitative Solutions team within the Global Strategy & Capital Allocation business unit.

Responsibilities

• Develop new and maintain existing 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
• Contribute to the enhancements of existing and new quantitative models for public and private asset classes — including private equity, private credit, real assets, and infrastructure
• Develop analytics that further enhance GSCA’s capabilities to monitor asset allocation execution through internal mandates
• Support the development and integration of commitment pacing, cash flows, and NAV forecasting models that integrate private markets into the total portfolio construction and glidepath allocation modeling
• Source, evaluate, and integrate private markets data from providers such as PitchBook, Preqin, Burgiss, and internal systems, building clean and reliable data pipelines and analytics
• Participate in GSCA cross‑team research projects across portfolio strategy and total portfolio management contributing to the team’s collective knowledge base and decision‑making process
• Partner with LMI Investment Business Units to institutionalize analytics and data

Qualifications

• Master’s degree in Financial Engineering, Statistics, Mathematics, Economics, Operations Research, or a related field plus 2+ years of experience in a quantitative research or related role
• Working knowledge of fixed income assets, public equities, and private markets, including private credit, real assets, infrastructure, or private equity
• Strong applied quantitative skills, including experience with simulation techniques, statistical modeling, time series analysis, and optimization, with the ability to build and maintain production‑ready research tools
• Demonstrated knowledge of private asset classes, including private equity, private credit, real assets, or infrastructure, with 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, with experience using version control (Git) and comfort working with large, messy, and non‑standardised datasets typical of private markets

Pay Philosophy: The starting salary range for this role is tailored to skills, experience, education, certifications, and location. Compensation may include base salary, bonuses, and other incentives.

At Liberty Mutual, we create a workplace where everyone feels valued, supported, and can thrive. We build an environment that welcomes a wide range of perspectives and experiences, embedding inclusion in every aspect of our culture.

Liberty Mutual is an equal opportunity employer. We will not tolerate discrimination on the basis of race, color, national origin, sex, sexual orientation, gender identity, religion, age, disability, veteran's status, pregnancy, genetic information or on any basis prohibited by federal, state or local law.

Fair Chance Notices