Lead Data Scientist

Role Overview

As a Lead Data Scientist at Brigit, you’ll build, improve, and maintain core machine learning models that power the company’s financial services. You’ll work on credit risk, early fraud detection, and transaction timing optimization, leveraging rich structured data to deliver measurable impact.

Responsibilities

• Build, test, and deploy new underwriting and risk models to improve prediction of customer risk.
• Own the full ML lifecycle from conception through production, including validation and monitoring.
• Develop and roll out models for fraud and payments.
• Contribute to best practices for feature development, model training/testing, and ongoing monitoring.
• Analyze shifts in the customer base as it grows and identify opportunities to improve outcomes.
• Collaborate cross-functionally with Data Science, Analytics, Product, and Engineering.
• Mentor junior data scientists and support aspiring data scientists on the team.

Requirements

• 6+ years of data science experience (modeling + analysis).
• Advanced degree in data science, statistics, computer science, or related field.
• Strong ML expertise (principles and techniques).
• Proficiency in Python with standard modeling/data tools (e.g., scikit-learn, JupyterLab, pandas, matplotlib, statsmodels).
• Ability to write complex SQL and combine multiple data sources.
• Experience creating training datasets, training models, tuning hyperparameters, validation, and A/B testing in production.
• Proven ability building classification/prediction models and iterating in a startup environment.
• Ability to communicate clearly with cross-functional partners (Engineering, Product, Business).
• Experience delivering end-to-end data science solutions: ideation → deployment → A/B testing.

Nice to Have

• Strong passion for optimizing/testing/improving models and operating through ambiguity as a self-starter.