Coda SearchStaffing
Associate, Private Credit Risk, Data Science (New York)
Coda SearchStaffing, New York, New York, United States, 10261
A leading global credit fund is seeking an Associate to join its risk, data science team. This newly created role will focus on building and enhancing quantitative models, analytics, and data-driven frameworks to support the firms investment decision-making across its growing private credit platform.
This is an exciting opportunity for a highly analytical and collaborative individual to work at the intersection of finance, data science, and technology, with exposure to structured credit, private IG, and generative AI initiatives.
Key Responsibilities Develop and maintain quantitative models to evaluate the risk and return of complex structured credit investments Partner with deal teams and portfolio managers to apply data-driven analysis to investment and portfolio construction decisions Support modelling initiatives for the firms private investment strategies, including private investment-grade and asset-based finance Collaborate with cross-functional teams to explore applications of AI and machine learning within the investment process Contribute to ongoing innovation in risk analytics, valuation frameworks, and data infrastructure
Qualifications Bachelors or Masters degree in a STEM, quantitative finance, or data-science field from a top-tier university (PhD a plus) 35 years of experience developing quantitative models in Python (numpy, pandas, scipy, statsmodels, scikit-learn) Strong background in statistics, econometrics, and financial modelling Proficiency in SQL, Git, and Microsoft Office Experience with stochastic modelling, Monte Carlo simulations, or credit modelling a plus Exposure to generative AI applications preferred Highly collaborative, detail-oriented, and execution-focused
Compensation Base: 130k-160k Bonus: 20% - 30%
This is an exciting opportunity for a highly analytical and collaborative individual to work at the intersection of finance, data science, and technology, with exposure to structured credit, private IG, and generative AI initiatives.
Key Responsibilities Develop and maintain quantitative models to evaluate the risk and return of complex structured credit investments Partner with deal teams and portfolio managers to apply data-driven analysis to investment and portfolio construction decisions Support modelling initiatives for the firms private investment strategies, including private investment-grade and asset-based finance Collaborate with cross-functional teams to explore applications of AI and machine learning within the investment process Contribute to ongoing innovation in risk analytics, valuation frameworks, and data infrastructure
Qualifications Bachelors or Masters degree in a STEM, quantitative finance, or data-science field from a top-tier university (PhD a plus) 35 years of experience developing quantitative models in Python (numpy, pandas, scipy, statsmodels, scikit-learn) Strong background in statistics, econometrics, and financial modelling Proficiency in SQL, Git, and Microsoft Office Experience with stochastic modelling, Monte Carlo simulations, or credit modelling a plus Exposure to generative AI applications preferred Highly collaborative, detail-oriented, and execution-focused
Compensation Base: 130k-160k Bonus: 20% - 30%