Senior Data Scientist – Credit & Lending

Senior Data Scientist – Credit & Lending

Requirements

• Have 7+ years of experience in data science, ML, or analytical roles, with 2+ years in credit, credit risk, or lending
• Bring experience from fintechs, traditional banks, or card issuers — especially with B2B credit products like working capital lines, charge cards, or revolving credit (consumer lending experience is a plus)
• Understand credit risk modeling techniques: scorecards, supervised ML (e.g. logistic regression, gradient boosting), time series forecasting, portfolio monitoring
• Have built and shipped production-grade ML models in regulated environments, with a deep understanding of explainability, fairness, and compliance constraints
• Are fluent in SQL and Python, and familiar with data platforms like dbt, Spark, Airflow
• Are comfortable working with noisy, sparse, or proxy data, especially in the context of early product development
• Can operate independently, navigate ambiguity, and prioritize work for long-term impact

Responsibilities

• Own the design and development of ML and statistical models across the credit lifecycle: Underwriting & Risk Scoring, Exposure Estimation & Line Assignment, Portfolio Monitoring & Early Risk Detection
• Build production-grade models that comply with fairness, explainability, and regulatory standards, including adverse action, model documentation, and bias testing
• Partner with Credit, Product, Eng, Risk, and Ops to define and evolve credit policies, risk strategies, and approval logic
• Identify and derive high-signal features from third-party credit data (e.g., bureaus, open banking, accounting systems, revenue intelligence) and Mercury’s internal signals
• Design modeling infrastructure alongside our ML & GenAI engineering team as we build Mercury’s new ML platform
• Be a thought partner in credit strategy — proactively surfacing opportunities to expand access while managing risk

Preferred Qualifications

No preferred qualifications provided.