OShaughnessy Asset Management (OSAM) 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 youll get exposed to different cultures people and business development happening around the world.

OShaughnessy Asset Management (OSAM) operates independently as a Specialist Investment Manager and is a research and money management firm based in Stamford. Our approach to managing money is transparent logical and completely disciplined leading to longstanding relationships with our clients. We are a leading provider of Custom Indexing services via CANVAS. CANVAS is a platform offering financial advisors an unprecedented level of control and ease in creating and managing client portfolios in separately managed accounts (SMAs). Advisors can set up custom investment templates access factor investing strategies utilize passive strategies actively manage taxes and apply ESG investing and SRI screens according to the specific needs preferences and objectives of individual clients.

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Quantitative Research Analyst

OSAM is hiring a Quantitative Research Analyst to join our growing Research team. You will help enhance our portfolio optimization and tax-aware portfolio construction frameworks supporting both simulation and live portfolio workflows. You will collaborate with portfolio managers developers and researchers to ensure research insights translate efficiently into production systems. Strong coding proficiency in C# Python and SQL deep familiarity with data structures and algorithms and experience with quantitative modeling optimization and feature engineering are essential.

Location: Stamford CT or New York City or other nearby location (East Coast time zone preferred) with a hybrid or remote work schedule.

What are the responsibilities of the Research Team

The Research team is focused on optimization risk and tax research for the CANVAS platform in addition to understanding what drives security returns. Our research is a scientific process using the combination of statistics and computer science applied to finance. The guiding philosophy of the firm is Learn Build Share Repeat. The research team is dedicated to this evolutionary cycle.

How You Will Add Value

You will conduct investment research: projects will involve running simulations of investment strategies to determine after-tax effects. Projects may include identifying measuring and implementing potential improvements to any aspect of OSAMs investment process.

• You will run large-scale simulations and backtests to assess strategy efficacy and after-tax implications.

• You will interact with robust data pipelines and APIs using C# Python and SQL ensuring data quality reproducibility and efficient computation.

• You will support integration of research outputs into production portfolio management systems used by PMs and traders.

• You will interface directly with portfolio managers risk teams and technology groups to communicate model results limitations and implementation details.

• You will apply statistical and machine learning methods (e.g. regression optimization NLP feature engineering) to generate validate and enhance alpha factors.

What Will Help You Be Successful in This Role

Candidates should have demonstrated ability to generate ideas and see them through a research cycle knowing how to prioritize and work collaboratively.Candidates should possess the following qualifications:

Education & Experience

• Degree in Computer Science Statistics Math Engineering Physics or Quantitative Finance.

• Masters or Ph.D. preferred for candidates with deeper specialization in quantitative methods data science or optimization.

• 2-5 years of relevant experience in quantitative research financial data engineering or software development for investment applications.

Programming & Data Skills

• Strong proficiency in C# (or Java) Python and SQL for data analysis modeling and production code.

• Experience with object-oriented programming and modular system design in a collaborative environment (Visual Studio Git).

• Deep understanding of relational databases schema design and query optimization.

Quantitative Methods

• Expertise in statistical modeling time-series analysis feature engineering and machine learning applications for finance.

• Knowledge of portfolio optimization risk modeling and factor-based investing.

Optimization

• Familiarity with convex optimization quadratic programming and constrained portfolio problems.

Soft Skills

• Excellent communication skills able to explain complex quantitative concepts to both technical and non-technical audiences.

• Highly organized detail-oriented and comfortable managing multiple concurrent research projects.

Compensation: Franklin Templeton offers employees a competitive and valuable range of total rewardsmonetary and non-monetary designed to supporttheir well-being and recognize their time talents and with base compensation employees are eligible for an annual discretionary bonus a401(k) plan with a generous match and recognition rewards. We also offer a comprehensive benefits package which includes a range of competitive healthcare optionsinsurance and disability benefits employee stock investment program learning resources career development programs reimbursement forcertain educationexpenses paid time off (vacation / holidays / sick / leave / parental & caregiving leave / bereavement / volunteering / floating holidays) and a motivational wellbeing program. We expect the base salary for this position to range between $110000 - $130000 depending on level of relevant experience and job location plus bonus.

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