Senior Data Scientist, Credit Strategy

SoFi•Cottonwood Heights, UT

22h•Remote

About The Position

SoFi Bank N.A seeks Senior Data Scientist, Credit Strategy in Cottonwood Heights, UT: Job Duties: Work in the Credit team 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. Collaborate with cross-functional teams such as Business Units Capital Markets, Product and Engineering, and use business knowledge and quantitative and analytical skills to drive revenue, control risk, and provide value to the company and consumers. Architect the pre-screen and underwriting strategies. Utilize deep analysis to 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. Responsible for innovation and embrace data-driven decisions. 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. Full-time telecommuting is an option.

Requirements

Master’s degree (or its foreign degree equivalent) in Data Science, Business Analytics or related quantitative discipline
Four (4) years of experience in the job offered or in a related occupation.
Consumer Lending Domain Expertise
Credit Strategy Analytical Lifecycle
Analytical Models
Programming & Analytical Tools (SQL, Python and Excel)
Analytical & Modeling Techniques (Decisions, Regression, A/B testing)
Data analysis and machine learning
Fintech and Risk Domain Knowledge
Tools for Data Visualization
Experience defining experimentation strategies.

Responsibilities

Analyze and evaluate data to develop and propose value-added credit risk strategies and models for SoFi's lending products.
Collaborate with cross-functional teams such as Business Units Capital Markets, Product and Engineering.
Use business knowledge and quantitative and analytical skills to drive revenue, control risk, and provide value to the company and consumers.
Architect the pre-screen and underwriting strategies.
Utilize deep analysis to power the future of lending with an optimal real-time data ecosystem.
Embrace data-driven decisions.
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.