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Salary: USD 152,000 - 190,000 / annual
Brex is an intelligent finance platform enabling companies to spend smarter and move faster across 200+ markets. The platform combines global corporate cards and banking with spend management, bill pay, and travel software, serving tens of thousands of companies including DoorDash, Coinbase, Robinhood, Zoom, and Plaid.
The Data organization develops infrastructure, statistical models, and products using financial data to drive decision-making, operational efficiency, risk management, and customer experience across the company.
As a Data Scientist II, you will own the complete machine learning lifecycle—from problem identification and stakeholder conception through model design, training, productionization, and monitoring. You'll drive Data & AI solutions from inception to deployment to manage risk and improve customer experience. You'll partner with cross-functional teams including Operations, Engineering, Product, Fraud, Compliance, and Credit to ensure models deliver measurable business impact.
Key responsibilities include:
- Driving end-to-end Data & AI solutions from conception through deployment
- Owning the full machine learning lifecycle: problem identification, model design, training, productionization, and monitoring
- Partnering with cross-functional teams across Ops, Engineering, Product, Fraud, Compliance, and Credit
- Circling back with stakeholders to inform product and strategic decisions based on model outcomes
Requirements:
- 3+ years of experience in Data Science/ML roles, OR 2+ years with a PhD in a quantitative field
- Demonstrated ability to own end-to-end model development, including productionization
- Expertise in Python programming, SQL queries, and ML-related frameworks
- Ability to apply statistical techniques such as hypothesis testing and A/B testing, with a statistical mindset
- Strong software engineering fundamentals, including API development and integrating ML systems into production services
- Strong communication skills and ability to collaborate with various stakeholders, both technical and non-technical
Nice to have:
- Experience working with real-time models
- Advanced degree (MSc/PhD) or published research in Machine Learning or related field
- Previous experience in risk domain (fraud, AML, credit) or building customer-facing ML models (suggestions/automations)
- Experience in the fintech industry
