Chase Consumer & Community Banking (CCB) serves consumers and small businesses with a broad range of financial services, including personal banking, small business banking and lending, mortgages, credit cards, payments, auto finance and investment advice. CCB Risk partners with each CCB sub-line of business to identify, assess, prioritize and remediate risk. Types of risk in consumer businesses include fraud, reputation, operational, credit, market and regulatory.
The Risk Modeling Team is a center of excellence within CCB Risk. We focus on statistical and machine learning (ML) techniques (including deep learning) to develop models that are used in credit risk assessment and fraud prevention. We are looking for candidates with demonstrated expertise in ML to join our talented team. The candidate will be responsible for end-to-end statistical and ML model development.
Success in this role requires a strong foundation in statistics and ML, coupled with experience in big data and distributed computing. The successful candidate will think like an analytic leader, collaborate with other teams, and communicate results effectively to senior management.
Risk Modeling - Data Scientist (VP)
Utilize statistical and machine learning techniques to lead model development for business banking models.
Steer models throughout their life cycle, including development, implementation, use, monitoring, and retirement.
Collaborate with partners in marketing, risk, technology, and model governance.
Qualifications
Minimum 8+ years work experience with 3 years of people management experience.
Masterâ„¢s degree from an accredited university in a quantitative field such as Computer Science, Mathematics, Statistics, Econometrics, or Engineering.
Experience in designing, building, and deploying production quality models, utilizing statistical and/or ML techniques.
Deep understanding of tuning and testing ML models (e.g., XGBoost, CNN, RNN)
Keyword: consumer%20banking
Chase Consumer & Community Banking (CCB) serves consumers and small businesses with a broad range of financial services, including personal banking, small business banking and lending, mortgages, credit cards, payments, auto finance and investment advice. CCB Risk partners with each CCB sub-line of business to identify, assess, prioritize and remediate risk. Types of risk in consumer businesses include fraud, reputation, operational, credit, market and regulatory.
The Risk Modeling Team is a center of excellence within CCB Risk. We focus on statistical and machine learning (ML) techniques (including deep learning) to develop models that are used in credit risk assessment and fraud prevention. We are looking for candidates with demonstrated expertise in ML to join our talented team. The candidate will be responsible for end-to-end statistical and ML model development.
Success in this role requires a strong foundation in statistics and ML, coupled with experience in big data and distributed computing. The successful candidate will think like an analytic leader, collaborate with other teams, and communicate results effectively to senior management.
Risk Modeling - Data Scientist (VP)
Utilize statistical and machine learning techniques to lead model development for business banking models.
Steer models throughout their life cycle, including development, implementation, use, monitoring, and retirement.
Collaborate with partners in marketing, risk, technology, and model governance.
Qualifications
Minimum 8+ years work experience with 3 years of people management experience.
Masterâ„¢s degree from an accredited university in a quantitative field such as Computer Science, Mathematics, Statistics, Econometrics, or Engineering.
Experience in designing, building, and deploying production quality models, utilizing statistical and/or ML techniques.
Deep understanding of tuning and testing ML models (e.g., XGBoost, CNN, RNN)
Keyword: consumer%20banking
