onsite
Investment Data Scientist - Python & Portfolio Analytics - Raymond James
Data Scientist
Data‑driven investment scientist crafting production‑grade Python models to optimize portfolios, automate workflows, and deliver actionable insights to investment committees.
About the role
Key Responsibilities
- Design, develop, and maintain production‑quality Python code for quantitative models that support investment decision‑making and portfolio management.
- Analyze large financial datasets to enhance portfolio construction methods and improve risk‑return trade‑offs.
- Implement statistical modeling and portfolio optimization techniques to generate actionable investment insights.
- Automate investment workflows, reporting, and data pipelines to increase efficiency and reduce manual effort.
- Collaborate with Investment Committee members, analysts, and stakeholders to translate business requirements into technical solutions.
Requirements
- Strong proficiency in Python, including libraries such as pandas, NumPy, scikit‑learn, and statsmodels.
- Experience with portfolio analytics, optimization, and statistical modeling in a financial context.
- Solid understanding of financial markets, instruments, and investment processes.
- Ability to write clean, maintainable, and well‑documented code suitable for production environments.
- Excellent communication skills and a collaborative mindset for working with cross‑functional teams.