Teams at Brigit

Lead development, deployment, and monitoring of underwriting, risk, fraud, and payments ML models. Own full modeling lifecycle, feature engineering, validation, A/B testing, cross-functional collaboration, and mentor junior data scientists.

Build, test, deploy, and monitor ML models for credit risk, fraud detection, and transaction timing. Create training datasets, run experiments and A/B tests, analyze customer trends, and collaborate with Engineering, Product, and Business teams to deliver end-to-end data science solutions.

The Senior Analytics Engineer will manage the analytics layer, owning dbt projects, orchestrating data pipelines, defining metrics, and ensuring data quality while mentoring the data team.