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 enterprisespanning 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. Were 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 Youll 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 610 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 Masters or PhD is preferred, though equivalent professional experience will also be considered.
San Francisco, CA $228,870 - $324,200 3 days ago
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