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 - $1 billion at a time. We’re proud of the recognition we’ve received, including being named one of Forbes’ America’s Most Promising Companies three years in a row, a 2012 World Economic Forum Technology Pioneer, and one of The World’s 10 Most Innovative Companies in Finance by Fast Company in 2013. We're conveniently located in downtown San Francisco, California.
Data, and lots of it, is at the core of Lending Club’s business. We use our rapidly growing dataset to understand the market, make credit decisions, predict performance, optimize ROI, and define product strategy. As part of the Data Solutions organization, the Principal Data Scientist will help us build of big data analytic capabilities as well as partner with various business departments to find new ways to use data to drive the business.
- Design and develop key metrics to measure product quality, business growth, loan performance, credit risk and investment returns.
- Partner with various business functions( operations, finance, credit, etc.) to formulate and define challenges, solve problems, and identify opportunities.
- Build data science models to understand the market, make credit decisions, optimize ROI, improve customer experience and engagement, and define product strategy.
- Present data science insights to business decision makers and suggest action items.
- Collabrate with engineers to implement data science models into production.
- 5+ years in Data Science—leveraging large data evnrionment, programmatic techniques and analytic methods to solve complex business problems.
- Advanced degree in mathematics, statistics, operation research, computer science or otherquantitative fields.
- Comprehensice knowledge in statistics and machine learning.
- Hands on/advanced experience with SQL, Stat packages (SAS, R, etc), and common data processing/programming languages (Python).
- Ability to explain data science insights to people with and without quantitative background
- Ability to contribute independently, as well as collaborate in a team.
- Nice to have: Big Data toolstack / experience.