Risk Modeler I

About the role

This position is part of the Risk Management department but supports the entire bank. The Model Development team challenges the status quo through statistical and machine learning (ML) powered predictive models covering the entire customer lifecycle, including Acquisitions, Underwriting, Fraud, Customer Management, and Collections.

As a Risk Modeler, you will participate in the end-to-end model development lifecycle for customer acquisition, credit risk, and underwriting. You will adopt applications of ML to enhance next-generation solutions and develop analytical tools to contribute to the strategic direction and financial performance of the organization. The role is also responsible for developing advanced machine learning frameworks that drive incremental growth in acquisitions.

Responsibilities

• Perform complex analyses and modeling that maximizes profits or asset growth and minimizes credit losses or other risk exposures.
• Serve as an expert consultant to senior management on highly complex issues.
• Manage the deployment of new models and the live testing or pilot programs derived from them.
• Monitor ongoing model performance to ensure stability and efficacy.
• Anticipate issues based on knowledge of business trends and propose direction and solutions.
• Provide peer review for other analysts within the team.
• Research the impacts of business decisions.
• Partner with technology groups to define business requirements.
• Provide analytic support to ensure company goals are met.
• Perform other duties as assigned.

Requirements

• Bachelor’s Degree in STEM (Science, Technology, Engineering, and Mathematics) or related field.
• Solid experience in using SAS, Enterprise Miner, R, Python, H2O, or similar tools and libraries to derive insights in a business setting.
• Intellectual horsepower with problem-solving and analytical skills.
• Knowledge of financial analysis and profitability drivers.
• Ability to quickly assimilate and analyze large amounts of information.
• Strong financial analytical skills with the ability to read, interpret, and evaluate financial time-series tracking reports (including vintage analysis).

Qualifications

• Preferred 2+ years of experience gathering data requirements for statistical, econometric, or predictive analytics research that drives market research/consumer analytics product innovation and implementation.
• Preferred 2+ years of experience in Financial Services, Credit Card Issuing, and Banking.
• Exposure to AI tool adoption.
• Consumer Credit Card industry experience.