Risk Manager, Model Risk Governance

Risk Manager, Model Risk Governance

Lending Club (NYSE: LC) opened in 2007 with one simple mission: create a more efficient, transparent and customer-friendly alternative to the traditional banking system that offers creditworthy borrowers lower interest rates and investors better returns. Today, we’re the world’s largest online credit marketplace, and we’re radically changing the way lending operates. We’re proud of the recognition we’ve received, including being named a World Economic Forum Technology Pioneer, a CNBC Disruptor 50, and one of The World’s 10 Most Innovative Companies in Finance by Fast Company. We’re conveniently located in downtown San Francisco, California.

Role Overview:

The successful candidate will have experience working in the consumer credit industry with a quantitative background in the development and validation and use of statistical modeling and loss forecasting models. This individual will perform independent validation of custom models built by our internal scoring group and review of all generic based models across all of Lending Club’s business lines. They will also manage the quarterly score model monitoring and annual review process. This role will help drive Lending Club’s model risk governance strategies and future development efforts. Another area of expertise that is important is the candidate’s experience working with credit reporting agencies attributes and data. This candidate will need to work collaboratively and successfully with many peers throughout our organization such as our various Risk Management teams, the Institutional Investor group, Legal & Compliance and our internal scoring team.


  • Review internally developed and third-party generic statistical models and scorecards for credit underwriting, loan pricing, loss forecasting, collections and backend review process.
  • Ensure all new statistical models are soundly developed, accurately back-tested and benchmarked and properly stress tested.
  • Ability to challenge developers and users and to elevate their findings for the overall improvement and acceptance of new models.
  • Consistently enhance our templates for model development and independent model validations and assist in maintenance of our Model Risk Governance centralize tracking system.
  • Assist in the overall ongoing maintenance and monitoring of all active models.
  • Perform various ad-hoc analyses relating to credit risk management initiatives and bureau data.
  • Work with 3rd party vendors and internal teams in reviewing and complete independent validations.


  • 3+ years of experience in model validation or predictive modeling (e.g., logistic regression, multivariate linear regression, decision tree, cluster analysis, etc.), familiar with other data mining/machine learning techniques is a plus
  • Consumer credit risk management experience is preferred
  • Understanding of Credit Bureau data desired
  • Ability to develop quantitative measurements/analysis to address multi-dimensional business needs
  • Ability to write model documentation clearly and concisely and support findings with reasonable foundations
  • Ability to communicate clearly and precisely on technical and business topics
  • Attention to details, dedicated, willing to take extra efforts
  • MS degree or PhD in quantitative/predictive analytics
  • SAS and SQL programing skill, working knowledge of SAS reporting is a plus
  • Experience with R or Python is a plus


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