Python Data Scientist / Quantitative Research Analyst – Fixed Income & Machine Learning

Python Quantitative Analyst – Machine Learning & Bond Analytics We are a small US-based investment management firm specializing in fixed income and structured products. We are looking for a highly analytical Python developer to work directly with the portfolio manager on building quantitative research tools and machine learning models for the bond market. We are looking for someone to become a long-term member of our research team. The engagement will begin as a freelance contract on Upwork (up to 40 hours/week) with the goal of transitioning to a full-time role for the right candidate. Responsibilities Develop Python tools for bond pricing, data analytics, and market research. Build machine learning and statistical models using large financial datasets. Analyze fixed income securities including agency MBS, CMBS, corporate bonds, ABS, and other structured products. Automate research workflows and improve quantitative trading models. Clean, organize, and visualize financial market data. Research new quantitative techniques that improve investment decisions. Required Skills Strong Python programming skills. Experience with machine learning, statistics, and data analysis. Strong analytical and problem-solving ability. Excellent written and spoken English. Comfortable working independently with a remote US-based investment team. Preferred (but not required) Bloomberg Terminal or Bloomberg API experience. Knowledge of fixed income, bond pricing, or capital markets. Experience with SQL, Pandas, NumPy, or time series analysis. About Us We're looking for someone who enjoys solving difficult quantitative problems and is curious about financial markets. You don't need to be an expert in bonds—we're happy to teach the market-specific knowledge to someone with a strong quantitative background and a willingness to learn. When Applying Please include: A brief summary of your experience. Links to your GitHub, portfolio, or sample Python projects (if available). A description of the most complex machine learning or quantitative project you've worked on. Your expected hourly rate. Your availability to overlap 6-8 hours with US Eastern Time.