Data Scientist (Applied Machine Learning)

• The Data organization develops infrastructure, statistical models, and products using financial data. Our Scientists and Engineers work together to make data —and insights derived from data — a core asset across the company. Our work is ingrained in Brex’s decision-making process, in the efficiency of our operations, in our risk management policies, and in the second-to-none experience we provide our consumers
• Drive Data & AI solutions from inception to deployment to efficiently manage risk and/or improve customer experience
• Be responsible for the full machine learning lifecycle — problem identification, model design, training, productionization, and monitoring
• Partner with cross-functional teams (Ops, Engineering, Product, Fraud, Compliance, and Credit)

Benefits

• Medical, dental & vision
• Generous vacation
• Spring Health & Calm
• Year-end company shutdown
• Milk Stork for nursing parents
• In-office days, lunches & offsites
• Commuter benefits
• 4 fully remote weeks
• Carrot Fertility benefits
• Generous parental leave- Expertise in Python programming, SQL queries, and ML-related frameworks
• Strong software engineering fundamentals, including experience with API development and integrating ML systems into production services
• Strong communication skills and the ability to collaborate with various stakeholders, both technical and non-technical
• Demonstrated ability to own end-to-end model development, including productionization
• Ability to apply statistical techniques such as hypothesis testing and A/B testing, and to approach problems with a statistical mindset
• 3+ years of experience in Data Science/ML roles, or 2+ years with a PhD in a quantitative field
• Experience working with real-time models
• Advanced degree (MSc/PhD) or published research in Machine Learning or a related field
• Previous experience in the risk domain (fraud, AML, and/or credit) or building customer-facing ML models (suggestions/automations)
• Experience in the fintech industry