Senior Credit Strategy Analyst

Responsibilities

• Design, implement, and optimize strategies spanning marketing, underwriting, model monitoring, fraud, loan sizing/terms, collections, and recovery
• Own policy development and changes, including testing, rollout, and post-implementation monitoring
• Analyze portfolio performance using SQL/Python and BI to OLS to identify trends, risks, and opportunities within key metrics
• Assess cost for new accounts originated, default rates, delinquency rates, loss rates, unit economics, repeat behavior, and churn
• Recommend proactive strategy adjustments based on emerging risks and opportunities
• Build and evaluate test-and-learn experiments, including A/B tests and DOE, across the customer lifecycle
• Isolate causal drivers of loss, delinquency, and recovery rates to control downside risk
• Partner with Data Science on model development, performance assessments, and model-strategy alignment across the customer lifecycle
• Translate technical findings into recommendations for senior leadership
• Present at company-wide quarterly business reviews (Q )
• Mentor junior analysts and establish best practices in credit-team data analytics
• Collaborate with Data Science, Engineering, Project Management, and Operations teams to develop scalable credit strategies

• Bachelor's Degree in an analytical/quantitative field (Math, Physics, Statistics, Engineering, Computer Science) from a competitive school.
• Elite quantitative & analytical skills.
• Proven ability to drive analytical projects and insights (3+ years experience)
• Strong proficiency in SQL and/or experience using Python for analysis (3+ years)
• Experience using advanced Microsoft Excel or Google Sheets analytics tools, including spreadsheet formulas, pivot tables, statistical add-ins, VBA, data management and merging tools (2+ years)
• Demonstrated experience in analyzing data to draw business-relevant conclusions and in data visualization techniques and tools.
• Ability to work in a fast-paced, collaborative environment
• Strong interpersonal, leadership, and communication skills
• Authorized to work for any employer in the United States; employment visa sponsorship is unavailable
• Advanced degree in an analytical/quantitative field (desired)
• 5+ years of experience in complex, data-driven problem solving, ideally within financial services, consulting, or a credit bureau (desired)
• Hands-on experience with credit bureau, alternative data, lead generation, and behavioral performance data (desired)
• Deep understanding of sub-prime credit dynamics including volatility, adverse selection, and risk layering (desired)
• Exposure to collections strategy or recovery optimization (desired)

Demonstrates expertise in data analysis and strategy optimization, utilizing SQL and Python to drive insights and recommendations. Proven ability to collaborate across teams and mentor junior analysts while effectively communicating complex findings to senior leadership.

• SQL Proficiency
• Python Analysis
• Data Visualization Techniques
• A/B Testing
• Credit Strategy Development

• Quantitative Analysis
• Data Analysis
• Statistical Modeling
• Portfolio Performance Assessment
• Cost Analysis
• Risk Assessment
• Data Management
• Spreadsheet Formulas
• Pivot Tables
• VBA

• Interpersonal Skills
• Leadership Skills
• Communication Skills
• Collaboration
• Mentoring

• Financial Services
• Credit Bureau
• Sub-Prime Credit Dynamics
• Collections Strategy
• Recovery Optimization

• Microsoft Excel
• Google Sheets
• Business Intelligence Tools
• Data Science Collaboration