Investment Data Scientist – Python & Portfolio Analytics (Hybrid)
Core
Develop, improve, and evaluate quantitative models to support investment decision-making and portfolio management.
Role type
Investment Data Scientist
Builds
Production-quality Python code, portfolio optimization algorithms, automated investment workflows, and interactive dashboards.
Domain
Quantitative finance and portfolio management
Deliverable
production ML models | product features | dashboards & analysis
Required skills
Python (pandas, NumPy, SciPy, CVXPY), statistical modeling (mixed integer programming, regressions, time series, Monte Carlo), data visualization (Streamlit, Tableau, Power BI, Plotly Dash), portfolio construction methods, risk modeling, financial data analysis
Preferred skills
Financial markets knowledge, performance measurement and attribution, Django framework, advanced investment concepts
Technologies
Python, pandas, NumPy, SciPy, CVXPY, Streamlit, Tableau, Power BI, Plotly Dash, Django
Responsibilities
Develop and maintain robust Python code for portfolio construction and automation; Design and implement portfolio optimization algorithms; Apply advanced statistical methods to extract insights from financial datasets; Collaborate with Investment Committee members and analysts to align model development with investment objectives; Build automated processes to eliminate manual tasks; Create interactive dashboards and visualizations to communicate analytical findings
Seniority
Mid-level, hands-on IC