Credit Data Scientist
We are seeking an experienced and analytically rigorous Credit Data Scientist skilled in credit modeling and data-driven decision-making efforts. You will play a crucial role in shaping our product and credit risk strategies by leveraging your expertise in predictive modeling, credit risk analysis, and scientific methodologies. Working closely with cross-functional teams—including Product, Engineering, Marketing, Sales, Finance, and Data Science—you will design and deploy innovative data science solutions to drive impactful, data-informed decisions at scale.
In This Role, You Will:
- Collaborate with cross-functional teams to shape credit and product strategies, applying scientific rigor to solve complex business problems.
- Design, implement, and launch innovative statistical, machine learning, and econometric models to measure results, predict outcomes, and identify causal impacts across products.
- Lead the development and deployment of credit risk models to minimize losses, improve prediction accuracy, and optimize credit performance.
- Interpret and analyze experimental results, developing key metrics and performance indicators for credit products.
- Drive the collection of new data sources and refine existing datasets to improve model accuracy and decision-making.
- Serve as the go-to expert for credit insights, engaging with regulators, engineers, data architects, and other stakeholders.
- Create compelling analyses and data-driven narratives that inspire strategic action across teams.
We’re Looking For Someone With:
- Experience & Expertise: 5+ years in data science, credit modeling, or risk management, ideally within a major bank or fintech environment, with a demonstrated ability to influence credit trends and make high-impact decisions.
- Credit-Specific Skills: Hands-on experience with credit risk modeling, a deep understanding of consumer credit dynamics, and a track record of optimizing credit portfolios and improving model metrics (AUC/ROC/KS).
- Statistical and Machine Learning Skills: Expertise in statistical analysis, machine learning, experimental design, and econometrics.
- Technical Proficiency: Advanced knowledge of Python, R, and SQL, with experience designing and deploying models in production environments.
- Educational Background: Master’s degree or Ph.D. in a quantitative field such as Computer Science, Mathematics, Engineering, Economics, or related discipline.
This role offers a unique opportunity to shape the future of credit products through data science, with the potential to make a significant impact on our business and customer outcomes. Join us in our mission to drive innovation in credit management and data-driven product strategy.
