About the role
The Data Science Manager owns the development, deployment, and lifecycle management of Clicklease’s credit, fraud, and portfolio models, translating business problems into production-ready modeling solutions that drive measurable risk and financial outcomes.
What you’ll be doing:
- Lead end-to-end development and lifecycle management of credit, fraud, and portfolio models, including PD, LGD, CNL/CGL forecasts, BAV cash flow scoring, fraud/identity scoring, and collections/recovery models
- Serve as hands-on technical lead on the most complex and highest-impact modeling projects, setting standards for experimental rigor, feature engineering, validation methodology, and documentation
- Manage, mentor, and develop the Data Science team, including performance management, coaching, hiring, and prioritization
- Own model governance across the portfolio, including documentation, validation artifacts, backtesting, challenger frameworks, and drift monitoring
- Partner with Data Engineering to design and maintain feature store architecture, training/serving pipelines, and data quality standards
- Translate business questions from Credit Risk, Collections, Finance, Operations, and Sales into well-scoped modeling projects and executive-ready recommendations
- Drive evaluation and adoption of new data sources and modeling techniques to improve decisioning quality
- Ensure compliance with fair lending, ECOA/FCRA, adverse action, and internal model risk standards
Essential Functions
- Design, develop, validate, and deploy predictive models that directly impact credit, fraud, and portfolio performance
- Lead and maintain model governance practices, including monitoring, backtesting, and compliance validation
- Manage and develop team members, including hiring, coaching, and performance evaluation
- Translate complex analytical outputs into actionable business recommendations for senior stakeholders
- Ensure adherence to regulatory requirements, including fair lending and adverse action compliance
- Design and evaluate experimentation frameworks (A/B/C/D tests, pricing tests, strategy rollouts) with proper statistical rigor and causal inference
- Represent the Data Science function in executive and cross-functional forums, translating technical outcomes into business impact
Minimum Requirements
- 7+ years of experience in data science, machine learning, or quantitative modeling
- 2+ years of experience leading projects or mentoring data scientists
- Experience building and deploying production models in a regulated financial services environment
- Experience using Python (pandas, scikit-learn, XGBoost or LightGBM) for model development
- Experience writing and optimizing SQL queries for analytical workflows
- Experience with full model lifecycle including feature engineering, validation, deployment, and monitoring
- Experience presenting analytical findings and recommendations to cross-functional stakeholders
- Bachelor’s degree in a quantitative field or equivalent practical experience
Preferred Qualifications
- Experience in consumer, small business, or specialty finance lending
- Familiarity with ECOA, FCRA, Reg B, and fair lending requiremen