Senior Quantitative Analyst, Quantitative & Risk Analytics

Fiduciary Trust International is a premier investment and wealth management firm with a commitment to growing and protecting wealth across generations. We offer a dynamic and collaborative approach to managing wealth for high-net-worth and ultra high-net-worth individuals and families, family offices, endowments, foundations, and institutions. Our investment managers, tax and estate planning professionals work together to develop holistic strategies to optimize clients’ portfolios while mitigating the impact of taxes on their wealth. As a fiduciary, the guidance we provide is in the best interests of our clients, without conflict or competing benefits. We offer boutique customization and deep expertise in specialized investment, tax and planning strategies alongside sophisticated technology and custody platforms.

Fiduciary Trust International is owned by Franklin Templeton, a dynamic firm that spans asset management, wealth management, and fintech, giving us many ways to help investors make progress toward their goals. With clients in over 150 countries and offices on six continents, you’ll get exposed to different cultures, people, and business development happening around the world.

Our Quantitative and Risk Analytics group is hiring a Senior Quantitative Analyst to report to the Investment Director of Quantitative and Risk Analytics. 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 & model operations, and software development. You will analyze portfolio, market, and risk data to generate insights for portfolio managers, while also maintaining proprietary datasets, models, and analytics infrastructure to support those insights. You will act as a partner to Portfolio Management and Research, translating investment questions into quantitative analysis, clear interpretation, and scalable analytical workflows.

Given rapid technological change—including the adoption of AI and automation in investment workflows—the candidate will be comfortable modernizing legacy processes, integrating AI-enabled capabilities, and building production-quality analytics that scale without sacrificing analytical rigor.

Hiring Location Options:

• Greater Boston Area (Lincoln, MA) or New York City
• Hybrid schedule: work onsite 3 days per week

• 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.

• Bachelor’s degree in a quantitative discipline (finance, economics, mathematics, statistics, engineering, computer science, or related field).

• 6–8 years of relevant experience in investment analytics, quantitative research, risk, portfolio analytics, or a closely related role.

• Strong programming skills in Python and demonstrated ability to translate analysis into production-quality code.

• Strong data skills, including SQL and experience working with large, real-world datasets; ability to build repeatable, well-controlled analytical workflows.

• Strong Excel skills, including experience with complex workbooks and VBA, for analysis, prototyping, and interaction with existing tools and workflows.

• 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.

• 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, maintain, and explain existing analytical models.

• Experience using LLM-based tools to support research or development workflows, with an understanding of model risk and responsible AI practices.

• Progress toward or completion of CFA or FRM is a plus.

Additional: This role is intended for a hands-on, mid-level quantitative contributor with the analytical depth to derive insight from complex financial data, the independence to own core analytical processes end-to-end, the collaborative mindset to partner closely with portfolio managers and researchers, and the technical capability to modernize the platform as quantitative investment analytics increasingly incorporate automation and AI.

Compensation: Franklin Templeton offers employees a competitive and valuable range of total rewards—monetary and non-monetary — designed to support their well-being and recognize their time, talents, and results. Along with base compensation, employees are eligible for an annual discretionary bonus (delete as appropriate), a 401(k) plan with a generous match, and recognition rewards. We also offer a comprehensive benefits package, which includes a range of competitive healthcare options, insurance, and disability benefits, employee stock investment program, learning resources, career development programs, reimbursement for certain education expenses, paid time off (vacation / holidays / sick / leave / parental & caregiving leave / bereavement / volunteering / floating holidays) and a motivational wellbeing program. We expect the annual salary for this position to range between $160,000 - $185,000, depending on location and level of relevant experience, plus bonus.

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