Data Analytics Director, Fixed Income Strategy

There is a place for you at T. Rowe Price to grow, contribute, learn, and make a difference. ​ We are a premier asset manager focused on delivering global investment management excellence and retirement services that investors can rely on today and in the future. The work we do matters. We invite you to explore the opportunity to join us and grow your career with us.

The Fixed Income Strategy Director – Data Analytics resides within the Fixed Income Investments division and is a member of the Analytics & Data investment team. The individual works alongside portfolio managers, quantitative researchers and portfolio managers on the design and development of global analytics and data platforms.

Principal Responsibilities: Strategists design, create and maintain high quality analytics, data and model solutions through close partnership with quantitative research and portfolio managers. Additionally, associates in this role will consult with technology professionals to transition interim solutions to a production environment.

• Architect and implement a global analytics and data platform for FI quantitative research and portfolio management

• Develop solutions that leverage existing structures to meet the needs of the research-driven investment and analysis processes

• Identify and evaluate the most appropriate method/tool/dataset to address current and future investment needs

• Implement global infrastructure to support quantitative model development and back-testing

• Identify and partner with key vendors to provide cutting-edge data and capabilities to quantitative researchers and portfolio management

• Incorporate optimal practices for applying Machine Learning techniques to quantitative

• Collaborate with quantitative research and portfolio management staff to identify data and technology solutions for investment needs

• Serve as a quantitative data and technology SME for all investment capabilities

• Maintain and support legacy quant models or processes

• Collaborate with CDO and technology professionals on data cataloging, distribution and data quality efforts

• Provide oversight for quantitative projects to operations and technology teams

Required Qualifications:

• Typically a degree in a quantitative discipline (e.g., Computer Science, Engineering, Math, Physics) and 10+ years of progressive, related experience.

• Experience working with large, complex financial datasets

• Experience in developing solutions within the data management and analytics domain, with a strong understanding of project management principles and frameworks.

• Established track record of outstanding ability to architect and implement data solutions in quantitative environments (e.g., Matlab, R, Python, Java, C#, C++, etc.)

• Thorough knowledge in fixed-income analytics, along with the ability to apply the concepts to solve practical portfolio problems.

• Experience with 3rd party data platforms and providers (e.g. Barclays Live, Bloomberg PORT, BQuant, FactSet, JPM DataQuery, Haver, Citi Velocity, etc.)

• Working knowledge of portfolio management process

• Direct experience working with fixed-income portfolios in a buy-side or sell-side capacity

• Architect and implement a global analytics and data platform for FI quantitative research and portfolio management

• Develop solutions that leverage existing structures to meet the needs of the research-driven investment and analysis processes

• Identify and evaluate the most appropriate method/tool/dataset to address current and future investment needs

• Implement global infrastructure to support quantitative model development and back-testing

• Identify and partner with key vendors to provide cutting-edge data and capabilities to quantitative researchers and portfolio management

• Incorporate optimal practices for applying Machine Learning techniques to quantitative

• Collaborate with quantitative research and portfolio management staff to identify data and technology solutions for investment needs

• Serve as a quantitative data and technology SME for all investment capabilities

• Maintain and support legacy quant models or processes

• Collaborate with CDO and technology professionals on data cataloging, distribution and data quality efforts

• Provide oversight for quantitative