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The VP of Data Science will lead the vision and execution of predictive modeling initiatives that directly impact credit risk, servicing, pricing, and profitability strategies. This high-impact role requires a deep technical foundation, particularly in credit analytics, and experience working in a fast-moving, results-driven environment.
The role reports directly to senior leadership and manages a team of data scientists and analysts, including mid-level managers.
Key Responsibilities
- Provide technical and strategic leadership to the Data Science function
- Lead the design, development, and implementation of machine learning and statistical models, with focus areas in: credit risk modeling (e.g., underwriting, scorecards, portfolio risk), servicing optimization, pricing and profitability models
- Partner cross-functionally with teams in product, engineering, finance, and operations to translate data into strategic action
- Mentor and develop a high-performing team, including managing middle managers
- Ensure scalability, compliance, and operationalization of models in production environments
- Guide executive stakeholders through data-driven decision-making using clear business narratives
- Explore and evaluate emerging data sources and modeling approaches
Qualifications
- 10+ years of experience in data science or advanced analytics
- Strong track record of developing and deploying credit risk and profitability models within a financial services or related industry
- Technical expertise in machine learning, statistics, and data architecture
- Experience leading and scaling data teams, including management of managers
- Strong business acumen and ability to work with minimal ramp-up time
- Master's or PhD in a quantitative field such as Mathematics, Statistics, Computer Science, Economics, or related discipline
Seniority level
Employment type
Job function
- Job functionFinance and Information Technology
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Inferred from the description for this job
Medical insurance
Vision insurance
401(k)
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