Franklin Templeton
Overview
O’Shaughnessy Asset Management (OSAM) is a research and money management firm based in Stamford and is a Specialist Investment Manager. OSAM operates independently and is a leading provider of Custom Indexing services via CANVAS®. CANVAS® is a platform enabling financial advisors to create and manage client portfolios in separately managed accounts (SMAs) with customizable templates, factor investing strategies, passive strategies, tax management, and ESG/SRI screening according to client needs. OSAM serves clients globally with offices on six continents and clients in over 150 countries. For more information, visit www.osam.com. Quantitative Research Analyst
role available to join the Research team. Location: Stamford, CT or New York City, or other nearby location (East Coast time zone preferred) with a hybrid or remote work schedule.
Responsibilities
Contribute to portfolio optimization and tax-aware portfolio construction frameworks, supporting both simulation and live portfolio workflows.
Collaborate with portfolio managers, developers, and researchers to translate research insights into production systems.
Conduct investment research by running simulations of investment strategies to determine after-tax effects and potential improvements to OSAM’s investment process.
Run large-scale simulations and backtests to assess strategy efficacy and after-tax implications.
Interface with data pipelines and APIs using C#, Python, and SQL to ensure data quality, reproducibility, and efficient computation.
Support integration of research outputs into production portfolio management systems used by PMs and traders.
Communicate model results, limitations, and implementation details with portfolio managers, risk teams, and technology groups.
Apply statistical and machine learning methods (e.g., regression, optimization, NLP, feature engineering) to generate, validate, and enhance alpha factors.
Qualifications
Education & Experience Degree in Computer Science, Statistics, Math, Engineering, Physics, or Quantitative Finance. Master’s or Ph.D. preferred for deeper specialization. 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 (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 technical and non-technical audiences. Highly organized and detail-oriented, able to manage multiple concurrent research projects.
Compensation & Benefits Franklin Templeton offers a competitive total rewards package, including base salary, annual discretionary bonus, a 401(k) plan with a generous match, and a comprehensive benefits package with healthcare options, insurance, disability benefits, employee stock investment program, learning resources, career development programs, education expense reimbursements, paid time off, and a wellbeing program. The expected base salary for this position ranges from $110,000 to $130,000, depending on experience and location, plus bonus.
Hybrid .
Company Culture & Equal Opportunity Our culture emphasizes employee well-being, diverse perspectives, and opportunities for professional and personal growth. Most benefits vary by location; ask your recruiter about benefits in your country. Franklin Templeton is an
Equal Opportunity Employer . We evaluate qualified applicants without regard to protected characteristics. If you require accommodation during the search or application process, email accommodations@franklintempleton.com with details of the request, job title, and job number.
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O’Shaughnessy Asset Management (OSAM) is a research and money management firm based in Stamford and is a Specialist Investment Manager. OSAM operates independently and is a leading provider of Custom Indexing services via CANVAS®. CANVAS® is a platform enabling financial advisors to create and manage client portfolios in separately managed accounts (SMAs) with customizable templates, factor investing strategies, passive strategies, tax management, and ESG/SRI screening according to client needs. OSAM serves clients globally with offices on six continents and clients in over 150 countries. For more information, visit www.osam.com. Quantitative Research Analyst
role available to join the Research team. Location: Stamford, CT or New York City, or other nearby location (East Coast time zone preferred) with a hybrid or remote work schedule.
Responsibilities
Contribute to portfolio optimization and tax-aware portfolio construction frameworks, supporting both simulation and live portfolio workflows.
Collaborate with portfolio managers, developers, and researchers to translate research insights into production systems.
Conduct investment research by running simulations of investment strategies to determine after-tax effects and potential improvements to OSAM’s investment process.
Run large-scale simulations and backtests to assess strategy efficacy and after-tax implications.
Interface with data pipelines and APIs using C#, Python, and SQL to ensure data quality, reproducibility, and efficient computation.
Support integration of research outputs into production portfolio management systems used by PMs and traders.
Communicate model results, limitations, and implementation details with portfolio managers, risk teams, and technology groups.
Apply statistical and machine learning methods (e.g., regression, optimization, NLP, feature engineering) to generate, validate, and enhance alpha factors.
Qualifications
Education & Experience Degree in Computer Science, Statistics, Math, Engineering, Physics, or Quantitative Finance. Master’s or Ph.D. preferred for deeper specialization. 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 (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 technical and non-technical audiences. Highly organized and detail-oriented, able to manage multiple concurrent research projects.
Compensation & Benefits Franklin Templeton offers a competitive total rewards package, including base salary, annual discretionary bonus, a 401(k) plan with a generous match, and a comprehensive benefits package with healthcare options, insurance, disability benefits, employee stock investment program, learning resources, career development programs, education expense reimbursements, paid time off, and a wellbeing program. The expected base salary for this position ranges from $110,000 to $130,000, depending on experience and location, plus bonus.
Hybrid .
Company Culture & Equal Opportunity Our culture emphasizes employee well-being, diverse perspectives, and opportunities for professional and personal growth. Most benefits vary by location; ask your recruiter about benefits in your country. Franklin Templeton is an
Equal Opportunity Employer . We evaluate qualified applicants without regard to protected characteristics. If you require accommodation during the search or application process, email accommodations@franklintempleton.com with details of the request, job title, and job number.
#J-18808-Ljbffr