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Director, Data Science & Machine Learning

LendingClub
San Francisco, United Statesfull_timeVerifiedPosted 28 Apr 2026
💰 $245,000/yr($210,000/yr$245,000/yr)

About the role

Current Employees of LendingClub: Please apply via your internal Workday Account

LendingClub (soon to be Happen Bank) 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

LendingClub’s Risk and Decision Science organization is looking for a Director, Data Science & Machine Learning to lead the development and implementation of advanced machine learning and statistical solutions across our lending and deposit products. You will manage a team of experienced data scientists, working across key domains like credit underwriting, loan pricing, fraud detection, and marketing targeting.

You will play a central role in delivering scalable, interpretable, and compliant models that drive LendingClub’s business performance while collaborating closely with partners across Risk, Technology, Marketing, and Compliance.

What You'll Do

  • 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
  • Communicate complex technical concepts clearly and effectively to business leaders, senior executives, and oversight functions

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
  • 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
  • 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
  • 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

Work Location
San Francisco

The above locations are eligible offices for this role. The locations have been determined to foster in-person collaboration with this role’s team or the related business lines. We utilize a hybrid work model, and our teams are in-office Tuesdays, Wednesdays, and Thursday

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Company

LendingClub

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