Job Description
Our Quantitative and Risk Analytics group is hiring a Senior Quantitative Analyst in either Lincoln, MA (Greater Boston) or New York City. The team supports portfolio analytics, simulation-based frameworks, strategic asset allocation, and quantitative research for portfolio managers and investment research teams across asset classes. This role blends quantitative analysis, applied financial modeling, data and model operations, and software development. You will analyze portfolio, market, and risk data to generate insight for portfolio managers, while also maintaining and extending the proprietary datasets, models, and analytics infrastructure that support those insights. You will act as a day-to-day partner to Portfolio Management and Research, translating investment questions into rigorous quantitative analysis, clear interpretation, and scalable analytical workflows. How You Will Add Value - Serve as a primary quantitative partner for Portfolio Management and Investment Research—triaging and resolving analytical questions with speed, rigor, and clear communication. Maintain, validate, and enhance portfolio and risk analytics (risk decomposition, factor exposures, scenario/stress testing, attribution, and forecasting) used in investment decision-making. Analyze portfolio, risk, and market data to identify drivers of performance and risk; interpret results and communicate actionable insights, assumptions, and limitations to portfolio managers and research stakeholders. Own and maintain critical data pipelines and data-quality control processes that enable accurate portfolio analysis and quantitative modeling (holdings, exposures, market/fundamental data, reference data). Implement daily, weekly, and monthly data-quality checks, reconciliation, and exception management. Design and implement quantitative analytics in Python and SQL—ranging from exploratory analysis and model development to reusable libraries and automated production workflows—that improve insight, reliability, and efficiency. Support recurring deliverables such as quarterly investment analysis and reporting, ensuring analytical accuracy, reproducibility, and clear linkage between data, models, and conclusions. Contribute to quant research projects, including the annual Strategic Asset Allocation process: data preparation, simulation and backtesting, scenario analysis, and presentation of results. Evaluate and integrate AI-enabled capabilities to enhance analytical workflows, with appropriate controls, validation, documentation, and adherence to compliance and data privacy requirements. Maintain strong operational documentation, version control, and operational readiness for quantitative models and the supporting analytics software stack. What Will Help You Be Successful in This Role - Bachelor’s degree in a quantitative discipline 6–8 years of relevant experience in investment analytics, quantitative research, risk, portfolio analytics, or a closely related role. Strong programming skills in Python; ability to translate analysis into quality code. Strong data skills, including SQL and experience working with large datasets. Strong Excel skills, including experience with complex workbooks and VBA, prototyping, and interaction with existing tools. Demonstrated ability to reason quantitatively about financial data, critically assess model outputs, and explain results, assumptions, and limitations clearly. Working knowledge of multi-asset investing and risk concepts (e.g., duration and curve risk, equity and credit risk drivers, diversification, scenario analysis). Comfort with modern software engineering practices, including Git-based version control, testing, and clear documentation. Excellent attention to detail, strong ownership mindset, and the ability to manage multiple priorities in a deadline-driven environment. Strong written and verbal communication skills; ability to engage effectively with non-technical stakeholders. Ability to work in the United States without sponsorship. We are unable to provide visa sponsorship/transfer for this position, now or in the future. Other Preferred Qualifications - Experience with investment and market data platforms such as FactSet and Bloomberg; familiarity with portfolio accounting and holdings data is a plus. Experience with cloud or modern analytics tooling (e.g., AWS, Azure, Snowflake). Experience building analytical dashboards or reporting layers (e.g., Tableau, Power BI, or Python-based visualization applications). Exposure to quantitative or statistical modeling techniques used in portfolio analytics, forecasting, or risk analysis; ability to understand, ma