01Overview
Role Summary
Senior data science leader who owns the strategy, roadmap, and delivery of the machine-learning and statistical models that power our consumer lending business. You will lead the development of credit risk models for underwriting and portfolio risk decisioning, while also overseeing models across fraud risk, marketing response and propensity, customer lifecycle management, collections prioritization, account management, and pricing, line, and offer optimization. This is a hands-on, technically fluent leadership role: you will set analytical standards, build validation-ready and well-documented models, mentor and grow a team of data scientists and ML practitioners, and partner with credit, fraud, marketing, and collections leaders who own policy and business strategy. You are the modeling and data science authority who turns data into reliable, governed, production-grade models.
Key Responsibilities
Own the model development strategy and roadmap across consumer lending decisioningcredit risk underwriting and portfolio risk models, as well as fraud, marketing, customer lifecycle, collections, account management, and pricing/line/offer optimization use cases.
Lead, hire, coach, and grow a team of data scientists and ML practitioners; set technical direction, performance expectations, analytical standards, and career paths while staying hands-on enough to review code, methodology, and model design.
Direct the end-to-end model lifecycleproblem framing, data and feature engineering, model development, validation-ready documentation, deployment, monitoring, recalibration, and retirementwith transparent, repeatable standards.
Drive feature engineering and the evaluation of alternative and third-party data sources (bureau, alternative credit, cash-flow/bank, device, and identity signals), quantifying lift, cost, stability, and compliance trade-offs.
Establish and govern champion/challenger experimentation, backtesting, and holdout frameworks to measure model impact .
