VP, Modeling & Data Science - San Francisco, CA

VP, Modeling & Data Science – San Francisco, CA

We are seeking an innovative and highly experienced quantitative data science leader to join us as our VP, Modeling & Data Science. This pivotal role will shape the next generation of modeling strategies across our enterprise—spanning personal loans, auto, purchase finance, and deposits.

As a key member of the leadership team, you will be responsible for setting a clear strategic vision for modeling excellence, including integrating next-generation machine learning (ML), AI capabilities, and advanced data sources into our credit, fraud, and marketing ecosystems. We’re looking for a leader with extensive experience in the consumer lending or Fintech industry who is passionate about leveraging advanced analytics and machine learning to solve complex business problems. You will lead a high-performing team of modelers and partner cross-functionally to build an agile, future-ready modeling infrastructure.

What You’ll Do

• Set the enterprise modeling strategy across key domains: credit underwriting, fraud detection, marketing targeting, pricing, and operational decisioning.
• Champion AI/ML model innovation and oversee deployment of advanced statistical and ML models across our ecosystem.
• Drive the development, enhancement, and governance of a comprehensive suite of models, ensuring performance, interpretability, and compliance.
• Collaborate with Technology to evolve our machine learning platform for scalable experimentation, deployment, and monitoring.
• Lead a team of 6–10 seasoned modeling and data science professionals, fostering a culture of innovation, curiosity, and rigor.
• Build robust partnerships with cross-functional teams including Credit Strategy, Marketing, Risk, Operations, Engineering, and Compliance.
• Evaluate and integrate emerging data sources to unlock new insights and opportunities across our lending and deposit products.
• Set the agenda for continuous improvement in tools, technologies, and methodologies.
• Serve as a modeling thought leader, representing us in industry forums and regulatory discussions, and benchmarking best-in-class practices.
• Partner closely with Model Risk Management to ensure strong governance and alignment with evolving regulatory expectations.
• Communicate complex technical and business topics with clarity and impact to senior leadership, the board, and regulators, on all aspects pertaining to the management of the modeling/AI/ML function.

About You

• 15+ years of relevant business experience, with a significant portion in consumer lending.
• 10+ years of experience leading and developing teams of modelers, data scientists, or other analytical functions.
• Extensive hands‑on experience with predictive modeling methods (e.g., logistic regression, multivariate linear regression, decision tree, cluster analysis), with a strong command of a wide range of advanced data mining and machine learning techniques.
• Deep practical experience and solid understanding of machine learning and deep learning methods (e.g., GBM, Neural Networks).
• Proficiency with leading machine learning and deep learning toolkits (e.g., TensorFlow, PyTorch, NumPy, Scikit‑Learn, Pandas).
• Experience establishing or scaling enterprise‑level ML platforms and practices.
• Experience with consumer credit portfolios and data science/decision science/risk management within the banking sector is a significant plus.
• Hands‑on knowledge of credit and fraud functions development in a regulated banking or fintech environment.
• Strong understanding of model governance, validation, and regulatory compliance in financial services.
• A systems thinker who is comfortable operating in both strategic and technical dimensions.
• Ability to develop sophisticated quantitative measurements and analyses to address multi‑dimensional business needs.
• Exceptional communication skills, with the ability to clearly and precisely articulate technical and business topics across all levels of management, including senior executives and regulators.
• Proven ability to influence and drive change cross‑functionally, championing new ideas and approaches.
• Degree in a quantitative field (e.g., Statistics, Computer Science, Engineering, Economics); a Master’s or PhD is preferred, though equivalent professional experience will also be considered.

San Francisco, CA $228,870 - $324,200 3 days ago