Machine Learning Engineer - Financial Data

About this role

## About Clair

If you can send your friends money in seconds, why does it still take your employer two weeks to send your paycheck?

At Clair, we are on a mission to create financial freedom for America's workers by giving them a digital banking platform that allows them to get paid as soon as they clock out of work. But we're not just another digital bank or on-demand pay provider. We meet Americans at their place of work by embedding our products within the scheduling, workforce management, and payroll apps they already use every day.

Learn more about us at getclair.com/about

### About the Role

As a Machine Learning Engineer on Clair’s Data team, you will be responsible for transforming diverse financial data sources, including but not limited to Plaid transactions, into production-grade features, predictive signals, and modeling pipelines that power Clair’s credit and underwriting systems.

Your work will focus on building the core feature layer that our credit models depend on: extracting structure from messy financial data, designing robust predictive features, forecasting key user-level events (such as income timing or financial stability indicators), and ensuring that these features are efficiently deployed, monitored, and continuously improved.

In addition to hands-on modeling and feature engineering, you will contribute to the development of Clair’s Data Science platform – building tooling, automation, and infrastructure that make it easier to train, deploy, and monitor ML systems at scale.

This role is ideal for someone who loves crafting meaningful features out of raw data, scaling ML systems in production, and driving the technical foundations of a modern financial ML stack.

### Key Responsibilities

• Engineer high-quality features from financial and behavioral data to support credit modeling.
• Build and maintain scalable pipelines for feature computation, income detection, and financial signal extraction.
• Develop forecasting and p...