VP, Risk & Quant Analytics — Tax‑Aware Portfolio Optimization

Franklin Templeton; New York (NY); Hybrid; USD 150,000 - 165,000; Full time

Benefits offered by this job

Discretionary bonus

401k plan

Health insurance

Job summary

Franklin Templeton seeks a Vice President Risk & Quantitative Analysis to advance Canvas’s quantitative capabilities, blending portfolio construction, risk analytics, and tax-aware investing. You will influence portfolio outcomes across thousands of accounts, improving tracking accuracy and tax efficiency while working across Portfolio Management and Research teams.

In this hybrid role based in Stamford, CT or NYC, you will build scalable analytics using Python (or C#), SQL, and related tech,

Qualifications

• 5+ years of experience in quantitative research or related investment role.
• Strong background in portfolio optimization, factor models, and direct indexing strategies.
• Proficiency in programming and data analysis (Python and SQL).
• Familiarity with risk analytics platforms like Barra and Aladdin.
• Experience evaluating or building tax-aware investment strategies, including tax-loss harvesting.

Responsibilities

• Validate optimization outputs and enhance tax-alpha methodologies.
• Collaborate with Portfolio Management and Research to evaluate model performance.
• Develop portfolio optimizations to validate outputs and analyze tracking error and tax-loss harvesting.

Skills

Quantitative research

Portfolio optimization

Python

SQL

Tax-aware strategies

Direct indexing

Risk analytics

Tools

Barra

Aladdin

Job description

Franklin Templeton seeks a Vice President Risk & Quantitative Analysis to advance Canvas’s quantitative capabilities, blending portfolio construction, risk analytics, and tax-aware investing. You will influence portfolio outcomes across thousands of accounts, improving tracking accuracy and tax efficiency while working across Portfolio Management and Research teams.

In this hybrid role based in Stamford, CT or NYC, you will build scalable analytics using Python (or C#), SQL, and related tech,