Tech Stack
NumpyPandasPythonScikit-LearnSQL
About the role
- Design, develop, and test statistical and machine learning models for credit risk areas (underwriting, fraud detection, portfolio management)
- Explore large datasets, identify patterns, and contribute to insights that inform credit strategies
- Help track how models perform over time, assist with validation, and support documentation to ensure compliance with governance and regulatory standards
- Partner with cross-functional teams (Product, Engineering, Credit) to integrate risk data science with product development and business strategy
- Take on meaningful projects, receive mentorship, and build presentation skills by sharing work with team members and senior leaders
Requirements
- Currently pursuing a Bachelor’s or Master’s degree in a quantitative field (Statistics, Mathematics, Computer Science, Economics, Engineering, etc.)
- Coursework or project experience with Python (pandas, scikit-learn, NumPy) and SQL
- Interest in statistics, machine learning, and problem-solving
- Excellent communication skills, both written and verbal, with a customer-focused mindset
- Eagerness to learn, collaborate, and take on new challenges