Machine Learning Engineer, Underwriting

This is a fully remote position, open to applicants in United States.

📋 Description

• As a senior individual contributor, you will be responsible for developing and enhancing the ML systems that support our products.

• You will engage in the complete modeling lifecycle, which includes problem formulation, feature development, training, calibration, experimentation, deployment, monitoring, and iteration.

• Construct, assess, and sustain underwriting and decision-making models.

• Create and refine underwriting decision frameworks, encompassing modeling, automation, policy logic, and amount assignment to manage exposure over time.

• Design and conduct experiments to assess model performance, evaluate impacts on approval rates and loss margins, and guide underwriting policy decisions.

• Acquire a comprehensive understanding of consumer behavior, repayment dynamics, and portfolio structure, utilizing this knowledge to inform model design and decision-making logic.

• Provide analysis and insights that guide portfolio-level decisions, including clarifying model behavior, trade-offs, and uncertainty to senior technical and business leaders.

• Create and uphold essential portfolio KPIs and a collection of periodic analyses to consistently identify risk and growth opportunities.

• Work collaboratively with Product, Engineering, Legal, Compliance, and Operations teams to ensure that underwriting systems align with business objectives and regulatory standards.

⛳️ Requirements

• A Master's degree in a quantitative discipline (e.g., Mathematics, Statistics, Physics, Computer Science, Operations Research).

• Over 5 years of experience applying AI, machine learning, or statistical modeling in decision-making contexts such as credit, risk, fraud, recommendations, or analogous fields.

• Familiarity with probabilistic models and decision systems, including calibration, score transformations, and the interpretation of model outputs.

• Proficient in experimentation: you understand how to design holdouts, measure lift, and assess models beyond just aggregate metrics.

• Experience in model monitoring, degradation detection, and retraining strategies within production systems.

• Extensive knowledge of underwriting practices that involve bank and cash flow analysis, bureau and alternative data, particularly with an emphasis on unsecured credit risk.

• Proven ability to explain modeling concepts, outcomes, and limitations to senior stakeholders and cross-functional teams.

🏝️ Benefits

• Flexible work arrangements

• Professional development