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As part of the AMS Research team, the Investment Data Scientist plays a key role in developing, improving, and evaluating quantitative models that directly support investment decision-making and portfolio management. This is a hands-on technical role focused on writing production-quality Python code to analyze financial datasets, enhance portfolio construction methods, and automate investment workflows.
Job Responsibility:
Develop and maintain robust Python code for portfolio construction, statistical analysis, and automation of investment workflows
Design and implement portfolio optimization algorithms
Apply advanced statistical methods to extract insights from financial datasets
Collaborate with Investment Committee members, analysts, and quant team members to align model development with investment objectives and operational needs
Build automated processes to eliminate manual tasks, reduce errors, and improve workflow efficiency
Create interactive dashboards and visualizations to communicate analytical findings
Requirements:
Bachelor’s degree in Computer Science, Mathematics, Statistics, Physics, Engineering, Economics, Finance, or a related quantitative field
3–6 years of hands-on experience with Python development and quantitative analysis
Demonstrated experience building optimization models, statistical systems, and/or automated workflows
Python libraries for data manipulation and array mathematics: pandas, NumPy, SciPy, and optimization libraries such as CVXPY
Statistical modeling and optimization: mixed integer programming, regressions, time series, and Monte Carlo simulation
Data visualization: Streamlit, Tableau, Power BI, Plotly Dash, or similar platforms
Quantitative finance: portfolio construction methods, risk modeling, and financial data analysis
Writing clean, documented, and version-controlled Python code
Translating business problems into quantitative models and technical solutions
Building and maintaining automated workflows
Creating clear, intuitive data visualizations for non-technical audiences
Validating and testing models to ensure accuracy and reliability
Performing performance calculations and financial data analysis
Nice to have:
Financial markets, investment products, and portfolio theory
Performance measurement and attribution methodologies
Django framework for database management
Advanced investment concepts and practices in the securities industry