
O’Shaughnessy Asset Management (OSAM) is part of Franklin Templeton, a forward-thinking asset manager that has built its success through powerful partnerships. We leverage cutting-edge strategies and deep insights to unlock opportunities for long-term wealth creation. Our talented, global teams bring expertise that is both broad and unique.
O’Shaughnessy Asset Management is a research and money management firm based in Stamford, Connecticut operating autonomously and backed with global, enterprise resources. Their approach to managing money is transparent, logical, and completely disciplined, leading to long‐standing relationships with clients. OSAM is a leading provider of Custom Indexing services via its Canvas® platform which offers financial advisors an unprecedented level of control and ease in creating and managing personalized separately managed accounts (SMAs) that target improved after-tax outcomes.
For more firm information, please visit www.osam.com
O’Shaughnessy Asset Management (OSAM), part of Franklin Templeton, is a quantitative investment firm that builds disciplined, transparent investment solutions for institutions and financial advisors. The Quant Technology team partners closely with researchers, portfolio managers, and developers to power data-driven investment strategies using modern platforms like CANVAS®. Team members collaborate in a highly technical, research-focused environment and gain exposure to cutting-edge portfolio construction, analytics, and financial technology.
For more information on our firm, visit our website, www.osam.com
Work directly with senior developers and research group to integrate and optimize research data processes and models
Design and develop in C#/Python/SQL in a stable and scalable manner.
Build robust data pipelines from many sources of varied levels of data quality, supporting both research demands, ad-hoc client analytic requests, and the core production applications.
Work with researchers, portfolio managers, and quants to implement, support, and run portfolio models.
Bachelor’s degree in computer science or related field of study.
Solid computer science fundamentals
Knowledge of data structures and algorithms
0-1 years of prior professional programming experience
C#, Python, and SQL scripting experience (SQL Server)
Working knowledge developing in MS Visual Studio (or VS Community editions)
Familiarity with proper source control practices (Git preferred)
Excellent communication skills to be able to interact with a wide range of users ranging from very technical (quants) to non-technical
Strong analytical skillset with demonstrated attention to detail
Quick learner with the ability to adapt quickly and work in a dynamic environment
Experience working in a financial services company, ideally in asset management
Experience working in a front office environment with researchers and portfolio managers
Advanced degree a plus
Familiarity with financial markets
Experience with DevOps practices, including CI/CD, and infrastructure-as-code
Working knowledge developing with Azure technologies
This role will work a hybrid schedule in our New York City office, 3 days/week
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, 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 $105,000 – $120,000, depending on location and level of relevant experience, plus discretionary bonus.
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