Senior Manager of Credit Risk, Upgrade

• This role requires a seasoned professional who can develop data driven credit risk strategies, pricing, loan amount and offer strategy frameworks, manage complex portfolios, and engage with executive leadership to ensure sound credit decision-making while supporting business growth objectives
• We are seeking a highly analytical and results-driven team member to join our team
• 7+ years of hands-on experience in a data analytics role, preferably in financial services
• Bachelor's degree in Statistics, Economics, Operations Research, Mathematics, Computer Science, Engineering or related quantitative discipline; advanced degree preferred
• Strong proficiency in SQL, Python (Pandas, Numpy), Tableau reporting, advance excel skills and Chaid decision trees (Knowledge seeker or R)
• Working with bureau attributes, proprietary model scores and feature engineering
• Detail oriented and strong analytical skill set
• Proactive, driven, and ability to work in a fast-paced environment

Desirable

• We are seeking an experienced Credit Risk Senior Manager to lead our credit risk management function for Personal Loan and drive strategic risk initiatives across the organization
• This is an individual contributor role with ownership over key strategic deliverables. The position offers the opportunity to broaden responsibilities over time based on business needs, performance, and demonstrated leadership
• This role will involve data-driven decision-making processes, manage credit risk projects from conception to deployment, tracking A/B test results and extracting insights that drive product development, risk mitigation, and customer strategy
• Analytical and results driven to solve business problems in areas like risk based pricing, loan amount assignment, acquisition credit risk underwriting, offer strategies and web funnel conversion initiatives
• Analyze large, structured and unstructured datasets using SQL, Python or similar tools
• Evaluate existing customer data, new third party or alternative data to enhance the feature list and work with data engineering and analytics teams to build scalable and durable feature engineering process
• Stay up to date with the latest trends and technologies in data science and fintech, actively research new tools and techniques available for model development
• Collaborate with cross-functional teams including risk, marketing, product, capital markets/investor relations, legal/compliance and engineering to define data-driven strategies