Staff Machine Learning Engineer, Credit Products (Square Financial Services)

Minimum of 8 years of related experience with a Bachelor's degree; or 6 years and a Master's degree; or a PhD with 3 years experience, with a focus on developing and deploying machine learning and statistical models in production environments.

Strong quantitative intuition and data visualization skills, with a proven ability to conduct sophisticated ad-hoc and exploratory analysis.

Full-stack proficiency preferred, including the ability to contribute across the entire technical stack—from data pipelines to production-grade software architecture.

Experience with tree-based models and gradient boosting is helpful but not required; we value the ability to adapt and learn new methodologies as the credit landscape evolves.

Block takes a market-based approach to pay, and pay may vary depending on your location.

Application Guidelines

The Credit and Lending team is responsible for the predictive intelligence that underpins Block’s primary capital-intensive products.

These products unlock unique access to credit for our customers, many of whom are otherwise underbanked and underserved by the traditional financial system.

As a Machine Learning Engineer within Square Financial Services (SFS), you will occupy a high-leverage role at the intersection of regulated banking and advanced autonomous systems.

This position requires full-stack ownership of the credit engine, from the curation of novel data signals to the implementation of the decisioning logic that drives Block’s top-line growth.

Our credit products are material drivers of the company’s profitability and are frequently highlighted in executive reviews and quarterly earnings reports.

We are seeking a scientifically-minded contributor capable of delivering extraordinary individual leverage to expand our underwriting capabilities into previously untapped segments through pragmatic policy evolution and advanced modeling techniques.