Develop, maintain, and enhance quantitative models and analytical tools that support asset allocation and portfolio construction decisions Produce scenario analysis, stress testing, and portfolio analytics to inform long-term, annual, and tactical investment decisions under insurance, regulatory, and rating agency constraints Support senior team members in monitoring portfolio positioning, risk budgets, liquidity, and projected investment cash flows Build and enhance expected return, risk, and relative-value models across asset classes in line with portfolio objectives and strategy Contribute to the further development of the team's expertise in private assets quantitative modeling, including return drivers, risk characteristics, and portfolio integration Support top-down macroeconomic and asset-class research across public and private markets Partner with LMI Investment Business Units (IBUs) to support data, analytics, governance and research initiatives that improve consistency, transparency, and decision-making Participate in cross-team research projects, sharing insights and contributing to the team's collective knowledge base Develop expertise in insurance-driven portfolio construction, private assets, and asset-liability management considerations through hands-on analysis and collaboration The position requires a Master's degree in Financial Engineering, Statistics, Mathematics, Economics, or a related field plus 5+ years of experience in the job offered or a related field.

Working knowledge of fixed income assets, public equities, and private markets, with exposure to private asset classes such as private credit, real assets, infrastructure, or private equity Understanding of long-horizon, balance-sheet-driven portfolio management, including the interaction between assets, liabilities, liquidity, and capital constraints Strong applied quantitative skillset, including time series analysis, simulation techniques, portfolio optimization, and performance attribution, with the ability to translate research into production-ready models and tools Advanced programming and data skills, including Python, SQL, version control, and familiarity with AI, machine learning (ML), and modern data architectures and analytics platforms

Experience: with financial and portfolio management systems and tools (e.g., Bloomberg, Black Rock Aladdin, Excel), and comfort working across the full technology project lifecycle Familiarity with private asset data providers and datasets and an understanding of their strengths, limitations, and appropriate use cases Comfort working with incomplete, noisy, or non-standardized data, applying sound judgment alongside quantitative rigor Demonstrated curiosity, ownership mindset, and willingness to proactively identify questions, test ideas, and iterate on models under guidance from senior team members Intellectual curiosity about the evolving role of AI in financial services, with a practical interest in experimenting with and applying new tools to improve research, analytics, and decision-making Strong communication and collaboration skills, with the ability to explain complex quantitative concepts clearly to a broad range of stakeholders and contribute effectively to cross-functional projects