Senior Data Scientist - Credit & Lending

Position Overview

• Location Type: Remote
• Employment Type: Full-time
• Salary: Not specified

As part of Mercury’s fast-growing Credit team, you’ll help build the foundational models, systems, and strategies that shape how credit decisions get made across our platform. Your work will directly influence our underwriting, risk, and credit operations — and be deployed into production to drive real outcomes. This is a rare opportunity to get in early on a high-impact ML role with massive whitespace, broad cross-functional exposure, and deep business influence.

Requirements

• Experience:
  • 7+ years of experience in data science, ML, or analytical roles.
  • 2+ years in credit, credit risk, or lending.
• Industry Experience:
  • Experience from fintechs, traditional banks, or card issuers.
  • Particularly with B2B credit products (working capital lines, charge cards, revolving credit).
• Technical Skills:
  • Fluent in SQL and Python.
  • Familiar with data platforms like dbt, Spark, Airflow.
  • Understanding of credit risk modeling techniques: scorecards, supervised ML (e.g. logistic regression, gradient boosting), time series forecasting, portfolio monitoring.
• Compliance:
  • Experience building and shipping production-grade ML models in regulated environments.
  • Deep understanding of explainability, fairness, and compliance constraints.

Responsibilities

• Model Development: Own the design and development of ML and statistical models across the credit lifecycle, including:
  • Underwriting & Risk Scoring
  • Exposure Estimation & Line Assignment
  • Portfolio Monitoring & Early Risk Detection
• Production Deployment: Build production-grade models that comply with fairness, explainability, and regulatory standards. This includes adverse action, model documentation, and bias testing.
• Cross-Functional Collaboration: Partner with Credit, Product, Eng, Risk, and Ops teams to define and evolve credit policies, risk strategies, and approval logic.
• Feature Engineering: 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.
• Infrastructure Design: Design modeling infrastructure alongside our ML & GenAI engineering team as we build Mercury’s new ML platform.
• Strategic Input: Serve as a thought partner in credit strategy, proactively surfacing opportunities to expand access while managing risk.

Company Information

The job description references Norman Borlaug and the “Green Revolution,” highlighting Mercury’s focus on building a strong and impactful financial infrastructure. It emphasizes a high-impact ML role with significant influence and exposure.