LendingClub's Risk and Decision Science organization is looking for a Director, Machine Learning & Data Science to lead the development and implementation of advanced machine learning and statistical solutions across their lending and deposit products to drive business performance.
Requirements
- 10+ years of experience in machine learning, data science, or credit risk analytics, preferably in consumer lending or financial services
- 5+ years of experience managing high-performing teams in applied machine learning or predictive analytics
- Strong technical expertise in supervised and unsupervised learning techniques (e.g., logistic regression, decision trees, GBMs, neural networks)
- Proficient in Python and key ML libraries (e.g., Scikit-learn, XGBoost, TensorFlow, PyTorch, Pandas, NumPy)
- Deep understanding of end-to-end model lifecycle management, from development through monitoring and retraining
- Familiarity with model governance practices and regulatory frameworks (e.g., SR 11-7, OCC guidance)
- Proven ability to execute complex projects, manage stakeholder expectations, and deliver high-impact results
Responsibilities
- Lead the end-to-end development, deployment, and performance monitoring of machine learning and statistical models used in credit, fraud, marketing, pricing, and operational decisioning
- Manage and mentor a team of data scientists and machine learning experts to deliver best-in-class modeling capabilities
- Partner with stakeholders across Credit Strategy, Marketing, Risk, Engineering, Model Risk Management, and Compliance to align solutions with business objectives and regulatory standards
- Apply advanced techniques such as gradient boosting, deep learning, and ensemble modeling to improve prediction accuracy and operational efficiency
- Contribute to the design and evolution of LendingClub’s ML infrastructure and tooling for scalable experimentation and deployment
- Identify and integrate new data sources to enhance model performance and business impact
- Ensure rigorous documentation, governance, and model validation in accordance with financial services regulatory requirements
Other
- You are an experienced and technically adept leader in machine learning and data science, with a passion for driving innovation and solving real-world financial challenges through data
- Excellent communication and data storytelling skills with the ability to influence across all levels of the organization
- Bachelor’s degree in a quantitative field (e.g., Statistics, Computer Science, Engineering, Economics); Master’s or PhD preferred
- Hybrid work model, with teams in-office Tuesdays, Wednesdays, and Thursdays.
- Primarily PT time zone requirements, with flexibility working across time zones when necessary.
