Director, Modeling and Data Science at Happen in San Francisco, CA

Job description

Current Employees of Happen Bank: Please apply via your internal Workday Account Happen Bank (formerly LendingClub) is built around a simple purpose: to clear the way to help people turn intention into action, and action into financial progress. That means offering focused products, a frictionless mobile-first experience, and clear terms with no gotchas. Respect and fairness is part of our DNA, and that ideal shapes how we work, how we treat each other, and how we invest in our employees and our community. Join us in using data, bold thinking, and a commitment to innovation to help clear the way for millions of Americans to achieve more. About the Role Happen Bank is looking for a Director, Modeling and Data Science to lead the machine learning and statistical models behind our lending and deposit products, including credit risk, fraud, collections, pricing, and marketing. You will lead a team of experienced data scientists and set the direction for how Happen Bank builds models that are accurate, interpretable, and compliant. You will work closely with partners across Risk, Technology, Marketing, and Compliance to turn those models into better decisions for the business and our members. What You'll Do Lead the end-to-end lifecycle of machine learning and statistical models, from development and deployment through monitoring and retraining, across credit, fraud, collections, pricing, and marketing decisioning Set the modeling roadmap and priorities for the function, balancing business impact, regulatory expectations, and team capacity Build, manage, and mentor a team of data scientists and machine learning experts, holding a high bar for technical rigor and accountability Partner with Credit Strategy, Marketing, Risk, Engineering, Model Risk Management, and Compliance to align solutions with business goals, and explain complex technical concepts clearly to executives and oversight functions Apply advanced techniques such as gradient boosting, deep learning, and ensemble modeling to improve model performance Shape Happen Bank's ML infrastructure and tooling for scalable experimentation and deployment, and identify new data sources that improve model performance Ensure rigorous documentation, governance, and validation in line with financial services regulatory requirements, including model risk and fair lending expectations Embed AI into how the team works, using it to speed up development, analysis, and documentation while keeping human oversight, data integrity, and accountability in place About You 10+ years of experience in machine learning, data science, or credit risk analytics, preferably in consumer lending or financial services, including 6+ years in people management; bachelor's degree in a related field; or equivalent work experience You lead the team with clear direction and sharp accountability, and you make sound calls on priorities, tradeoffs, and risk You have strong technical depth in supervised and unsupervised learning (e.g., logistic regression, decision trees, GBMs, neural networks) and are proficient in Python and key ML libraries (e.g., Scikit-learn, XGBoost, TensorFlow, PyTorch) You have a deep understanding of the model lifecycle, from development through monitoring and retraining You are familiar with model governance practices and regulatory frameworks (e.g., SR 11-7, OCC guidance) You understand how AI and ML models interact with credit risk decision-making, including their limitations, failure modes, and regulatory implications, and you know when a model should inform a decision versus drive it You have a clear perspective on where AI adds real leverage across your function and have turned it into how your teams operate, fostering a culture of innovation while keeping accountability sharp You have a proven record of delivering complex, cross-functional projects, managing stakeholder expectations, and bringing partners along as the work evolves Nice to Have Hands-on experience developing LLM and foun