Machine Learning Engineer

Responsibilities

• Build, evaluate, and maintain underwriting and decisioning models
• Design and evolve underwriting decision frameworks, including modeling, automation, policy logic, and amount assignment
• Design and run experiments to evaluate model performance and impact on approval rates, loss, and margin
• Develop a deep understanding of consumer behavior and repayment dynamics to inform model design
• Contribute analysis to inform portfolio-level decisions and explain model behavior to leaders
• Develop and maintain key portfolio KPIs and periodic analysis to identify risk and growth opportunities
• Collaborate with Product, Engineering, Legal, Compliance, and Operations to ensure systems meet business and regulatory goals

Requirements

• Master's degree in a quantitative field (Mathematics, Statistics, Physics, Computer Science, or Operations Research); PhD strongly welcomed
• 5+ years of experience applying AI, machine learning, or statistical modeling in decisioning contexts (credit, risk, fraud, or recommendations)
• Experience with probabilistic models, decision systems, calibration, and score transformations
• Strong experimentation skills including designing holdouts and measuring lift
• Experience with model monitoring, degradation detection, and retraining strategies in production
• Deep knowledge of underwriting using bank/cashflow analysis and bureau/alternative data for unsecured credit risk
• Ability to explain modeling concepts and limitations to senior stakeholders

Preferred Qualifications

• Fintech background
• Consumer finance experience in a non-large bank environment
• Experience with advanced modeling techniques
• Background in small to medium-sized companies