Systematic Fixed Income Researcher

Job Description:

The Group

Quantitative Research & Investments (QRI) is an investments and research division within Asset Management at Fidelity. We are responsible for the management and development of quantitative and hybrid quant/fundamental investment strategies and solutions while providing high quality quantitative, data-driven support to Fidelity's investment professionals, ensuring they have access to the most relevant data and advanced quantitative analysis.

The Role

Join the Systematic Fixed Income Strategies group within Fidelity's QRI team. We're looking for a curious, high-energy researcher who loves turning data into investable insights-and who writes clean, efficient code. In this role, you will design, test, and deliver active systematic strategies across global fixed income markets, partnering closely with Portfolio Management from idea generation through production execution.

The Value You Deliver

• Research and develop systematic strategies across global fixed income spanning asset allocation, timing, and security selection.
• Build robust research pipelines and backtests: define hypotheses, run backtests, evaluate signal efficacy/decay, and assess performance robustness and risk.
• Productionize research: transform prototypes into reliable, well tested code; design and maintain data pipelines; and ensure strategies are modeled and executed optimally.
• Collaborate with researchers, portfolio managers, and product partners across the full investment process-from idea generation to implementation and post trade review.
• Discover, evaluate, and integrate alternative and new datasets; engineer features from large, complex data (structured and unstructured).
• Drive implementation and execution research, portfolio construction, transaction cost modeling, PM dashboards, and attribution.

• Advanced degree in Engineering, Physics, Mathematics, Economics, Finance, Computer Science, or another quantitative discipline.
• 3+ years of relevant experience in systematic investing or a comparable quantitative research role.
• Demonstrated experience researching with large, complex datasets and translating research into production ready tools.
• Exceptional Python coding skills with fluency in the scientific Python stack, version control (Git), and unit/integration testing.
• Familiarity with relational databases.
• Very strong interpersonal and verbal communication skills; team oriented with a bias for action and ownership.

• Understanding of fixed income markets, including drivers of return, risk management, and portfolio construction techniques.
• Experience with portfolio optimization, risk models, and execution research.
• Experience with Bloomberg.
• Exposure to cloud and distributed compute (e.g., AWS, Spark), workflow orchestration, and CI/CD.