Staff Data Scientist, Credit Strategy

Role Overview

• Design and deploy innovative approval, qualification, and segmentation strategies that maximize application approval rates while achieving credit loss targets
• Develop and maintain underwriting policies that define minimum acceptance criteria and policy declines for segments outside Mulligan’s risk appetite
• Create statistically grounded credit limit assignment frameworks that optimize lifetime customer value while managing downside risk
• Design pricing and interest rate strategies, including testing frameworks, to ensure adequate loss coverage, strong borrower selection, and high customer take-up rates
• Optimize data collection strategies by balancing the information value of data against customer friction and operational cost
• Partner closely with the manual underwriting team to build a hybrid risk framework that integrates analytical strategies with expert manual review, ensuring consistent execution and continuous feedback loops
• Collaborate with Product, Engineering, and Data Science teams to design and deploy scalable infrastructure that enables rapid iteration and refinement of credit strategies
• Establish robust portfolio monitoring and reporting processes to track approval rates, credit performance, and risk metrics against expectations
• Apply a thoughtful, forward-looking approach to portfolio construction to ensure assets are resilient across economic cycles and attractive to debt investors on a risk-adjusted basis
• Incorporate macroeconomic trends and forward-looking risk signals into credit strategy to ensure ongoing relevance in evolving market conditions
• Performs other duties as assigned

Requirements

• 5+ years of relevant experience in commercial risk data science and credit strategy within a fintech or banking environment
• At least 3–4 years of hands-on experience designing, calibrating, and managing credit strategies for Merchant Cash Advance (MCA) products; prior MCA credit strategy experience is required
• Strong experience overseeing model deployment, execution, and monitoring within a production environment; ML Ops experience is highly preferred
• Master’s degree in Data Science, Statistics, Economics, Finance, or a related quantitative discipline required

Benefits

• Medical, vision, and dental benefits to support you and your family.
• Flexible Spending Accounts (FSA) for eligible healthcare and dependent care expenses.
• A 401(k) with matching contributions to help you plan for retirement.
• Paid time off, including sick leave, vacation, and holidays.
• Paid parental leave for growing families.
• A Lifestyle Spending Account (LSA) for athletic and wellness expenses.
• An employer-sponsored Life and AD&D policy, with options for additional coverage.
• A Learning Stipend for professional development activities.
• An Employee Assistance Program (EAP) and travel assistance services.
• Complimentary snacks and refreshments in the breakroom.
• A referral program that rewards you for bringing in top talent.
• Company events to connect, celebrate, and grow together.