Director, Data Science – Credit Risk & AI
RemoteUnited States
Job Summary
Own and execute the credit risk data science roadmap across underwriting, default, delinquency risk, fraud, profitability, portfolio performance, and loss forecasting. Lead and prioritize model development initiatives throughout the full lifecycle, including design, validation, deployment, monitoring, and performance management. Establish model governance standards, documentation requirements, and monitoring frameworks for credit decisioning. Partner with Credit Strategy, Risk, Compliance, IT, and external providers to translate business objectives into analytical strategies that improve decision quality and operational efficiency. Guide the application of machine learning, statistical modeling, and experimental frameworks to optimize credit policies. Oversee scalable modeling datasets, feature pipelines, and production environments while ensuring work supports independent validation, audit, and regulatory review. Lead responsible AI adoption to enhance analytical productivity and knowledge sharing. Communicate model strategy, risks, and tradeoffs to senior leadership and governance forums.
Required Qualifications
- Bachelor's degree in Mathematics, Statistics, Engineering, Computer Science, Data Science, or another quantitative STEM discipline
- 7 years of experience in consumer lending, fintech, banking, credit risk analytics, data science, or related quantitative field
- 3 years of experience leading data science, credit risk modeling, advanced analytics, or model governance initiatives, including demonstrated leadership of technical talent and/or complex analytical programs
- Demonstrated experience developing, deploying, monitoring, and governing models supporting underwriting, credit risk, fraud, profitability, portfolio management, or loss forecasting
- Advanced proficiency with SQL and Python
- Strong knowledge of machine learning, statistical modeling, and production model lifecycle management
- Strong understanding of model development documentation, monitoring, independent validation, audit, governance, and regulatory expectations within a lending or financial services environment
- Demonstrated ability to translate business problems into analytical solutions and evaluate model performance in the context of both risk and financial outcomes
- Proven ability to lead complex, cross-functional initiatives involving Credit, Risk, Compliance, IT, Data Engineering, Operations, and external partners
- Strong executive communication and influencing skills, with the ability to translate complex analytical concepts and model outputs into clear business insights, risks, tradeoffs, and recommendations
- Demonstrated ability to mentor and develop technical talent, establish analytical best practices, and raise technical standards across a team
- Demonstrated fluency with AI-assisted analytical, development, documentation, and productivity tools, including an understanding of responsible and governed AI use
- Must be able to sit for long periods of time
- Must be able to lift, push, or pull up to 20 pounds
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