About the Role
Brigit is a mission-driven financial health company dedicated to helping everyday Americans build a brighter financial future. As a Lead Data Scientist, you will play a pivotal role in scaling our impact by building, improving, and maintaining the mission-critical machine learning models that power our core services. From identifying credit risk and preventing fraud to optimizing payment timing, your work will directly prevent predatory fees and help over 100 million people living paycheck-to-paycheck gain access to fair, transparent financial tools.
We are looking for a technical leader who thrives on autonomy and ownership. In this role, you will have access to rich, structured datasets to derive deep insights and build complex models that solve real-world problems. You won't just be building algorithms; you will be setting best practices for our data science organization and collaborating closely with Product, Engineering, and Analytics teams to define the future of financial wellness.
Key Responsibilities- Full-Cycle Model Ownership: Lead the end-to-end modeling lifecycle, from initial ideation and feature engineering to production deployment and continuous monitoring.
- Risk and Underwriting: Design and roll out advanced underwriting models to more accurately predict credit risk, allowing us to support more members safely.
- Fraud and Payment Optimization: Develop and refine models to detect fraudulent activity early and optimize transaction timing to prevent customer overdrafts.
- Strategic Analysis: Analyze shifts in our expanding customer base to pinpoint growth opportunities and areas for product improvement.
- Technical Leadership: Establish and champion best practices for model training, hyperparameter tuning, validation, and A/B testing across the team.
- Mentorship: Act as a technical mentor for junior data scientists, fostering a culture of excellence and continuous learning within the data organization.
- Cross-functional Collaboration: Partner with Product and Engineering teams to integrate data science solutions into the core product experience.
- Experience: 6+ years of professional experience in data science, specifically focused on building and deploying predictive models.
- Education: Advanced degree (Master’s or Ph.D.) in Data Science, Statistics, Computer Science, or a related quantitative field.
- Technical Mastery: Proven expertise in machine learning principles and deep proficiency in Python using toolkits such as sklearn, JupyterLab, pandas, and statsmodels.
- Data Engineering: Strong ability to write complex SQL queries and synthesize data from multiple disparate sources to create robust training sets.
- Deployment & Testing: Demonstrated experience running A/B tests in production environments and managing model performance monitoring.
- Communication: Exceptional written and verbal communication skills, with a proven ability to translate complex technical concepts for non-technical stakeholders.
- Startup Mindset: A self-starter who thrives in ambiguity, moves quickly, and is passionate about using technology to drive social impact.
- Competitive Compensation: Annual base salary of $185,000 - $215,000 plus a 10% annual bonus opportunity and equity.
- Health & Wellness: Comprehensive medical, dental, and vision insurance, plus access to Headspace and Wellhub for mental and physical health support.
- Flexibility: A remote-friendly work environment with a flexible PTO policy to support work-life balance.
- Family Support: Robust paid parental leave to support our team members during major life transitions.
- Growth & Development: Annual reimbursement for professional learning and development, along with monthly stipends for wifi and cell phone expenses.
- Mission-Driven Culture: The opportunity to work in a high-growth, award-winning startup (Forbes Fintech 50, Fast Company Most Innovative) dedicated to financial equity.