Credit Risk Data Science Jobs in California (NOW HIRING)

The team

SoFi's Credit team manages credit risk activities for our lending products (Student Loan Refinance, Private Student Loan, Personal Loan, Credit Card, and Mortgage) - including credit strategies/policies for new account origination and portfolio management, collections/recovery strategies and operations, and risk and operational data science and analytics. The team designs data-driven strategies to ensure the growth in lending is consistent with the company's risk appetite and helps create the products and experiences that put our members' interests first.

The Senior Credit Manager will work in the Credit team and have responsibilities to analyze and evaluate data to develop and propose value-added credit risk strategies and models for SoFi's lending products, including Personal Loan, Student Loan Refinance, Private Student Loan, and Credit Card. The initial focus of the role will be on Personal Loan but the candidate may get opportunities to work on other lending products in the future. 

The candidate will be responsible for independently developing and implementing Personal Loan underwriting strategies that meet our risk appetite, monitoring and analyzing the risk trends within the portfolio to provide insights and recommendations for strategy enhancement opportunities. She/he will be part of the Credit team with 1LOD responsibilities.

The Senior Credit Manager will collaborate with cross-functional teams such as Business Units, Operations, Marketing, Finance, Capital Markets, Product, Engineering, Legal and Compliance. Use business acumen, credit experience and quantitative and analytical skills to drive revenue, control risk, and provide value to the company and consumers.

The ideal candidate will possess a data-driven analytics background and the strategic acumen to direct a function that draws strategic insights from data using database and statistical analysis tools to inform decisions and support SoFi's overarching strategic goals relative to loss prevention and profit optimization. They bring new ways of thinking, data sources, technologies, and capabilities to SoFi. 

What you'll do:

• Innovate... Bring your brightest ideas to build algorithmic risk strategies. This means you will architect credit underwriting, pre-screen targeting, and risk tier assignment.
• Data Driven... Your deep analysis will power the future of lending with an optimal real-time data ecosystem - including multi-product internal, bureau, third-party, and alternative data sources and uses.  
• Iterate, learn, innovate... We are all responsible for innovation and must embrace a test-and-learn mentality and data-driven decision making.
• Collaborate... Work collaboratively with business partners such as Business Units, Operations, Marketing, Finance, Legal and Compliance to deliver successful business results. Partner closely with implementation teams to accurately drive new strategies to production. 
• Control the Risk and Drive Performance Outcomes ... Understand credit risk and develop approaches to mitigate loss and responsibly grow revenue. Monitor the performance of strategies and portfolios. Document and communicate results and escalate issues as necessary. Identify gaps/opportunities and drive actions.  
• Challenge the Status Quo ... Challenge others, continuously raise the bar, build better processes and attack hard problems to help us build the best products in the industry. 
• Grow, Grow, Grow!... Be inspired by dynamic leaders and our rapidly growing business.  We want YOU to be an inspired leader of tomorrow, so we are recruiting the best, brightest, and passionately quantitative team members.  

What you'll need:

• 7+ years of unsecured credit risk and data science experience
• Business acumen and work experience in the consumer lending business (loans or credit cards)

• Direct experience in the credit strategy analytical life cycle, including strategy and decision tree development, P&L, presentation, implementation validation, and post-implementation monitoring

• Proven analytical skills in conducting sophisticated analysis using customer performance data, bureau attributes, and other 3rd party variables to solve business problems
• Advanced SQL and Python skills for segmentation and vintage analysis, PD/LGD/EAD risk modeling (e.g. decision trees, logistic regression) and back-testing, rapid prototyping, feature engineering and pipeline development/operationalization
• A demonstrated ability to synthesize and communicate analysis to business partners and senior management
• Results-driven analytical approach, eagerness to learn, and ability to work collaboratively in a fluid environment
• Statistically rigorous experiment design and inferential evaluation
• Experience in developing custom credit features using data sources such as internal cross-product data, bank transaction, and other alternative data
• Advanced degree (Master's or PhD) with a quantitative major such as Statistics, Mathematics, Engineering, or Computer Science