Job Summary Our client is seeking Data Science Quantitative Engineer to join their team! This position is located in Chicago, Illinois. Duties • Drive quantitative research from idea generation through to data acquisition, statistical analysis, and documentation of findings, with a particular focus on predictive alpha models • Develop and implement sophisticated fixed income investment models and trading strategies using a rigorous scientific approach • Integrate quantitative research findings into portfolio management, risk management, and trade execution processes to optimize investment outcomes • Enhance the investment process of the company's quantitative credit strategies • Conduct empirical research applying findings to signal creation, portfolio construction, and risk assessment • Utilize machine learning and AI techniques to innovate and refine investment strategies, leveraging technology to drive superior performance • Collaborate with team members and effectively communicate research findings within the organization and to external stakeholders, including clients and prospects Desired Skills/Experience: • Master's degree in a technical or quantitative discipline such as: statistics, mathematics, physics, electrical engineering, computer science, applied economics, or finance • 5+ years of relevant experience as a hands-on quantitative investment professional, with a track record of developing predictive alpha models in fixed income markets • Systematic Fixed Income investing experience a plus • Proficiency in at least one programming language, ideally Python, with additional experience in PySpark, SAS , MATLAB, or R being advantageous • Hands on experience working in Azure Cloud Services, ADLS, ADF, Databricks will be very helpful • Strong knowledge of asset pricing, factor anomaly literature, and the application of sustainability data within an investing context • Expertise across the entire quantitative investment lifecycle, including alpha research, risk management, portfolio management, trade execution, and the application of technology • Experience in applying machine learning models within an investing context, with familiarity in alternative data as an advantage • Ability to think independently, creatively approach data analysis, and clearly communicate complex ideas Benefits: • Medical, Dental, & Vision Insurance Plans • Employee-Owned Profit Sharing (ESOP) • 401K offered The approximate pay range for this position is between $47.00 and $67.00. Please note that the pay range provided is a good faith estimate. Final compensation may vary based on factors including but not limited to background, knowledge, skills, and location. We comply with local wage minimums.