Data Scientist, Brex

• The ideal candidate has experience leveraging product intuition and advanced analytics to understand customer behavior, measure product impact on revenue retention and growth, and derive insights through causal inference and predictive modeling
• They should also have a strong ability to translate data insights into actionable recommendations for product and business teams
• Master’s degree or Ph.D. in Statistics, Computer Science, Economics, or a related quantitative field
• 3+ years of experience in a data science, analytics, or related role focused on product analytics
• Strong experience with SQL and Python (or R) for data analysis and modeling
• Proficiency in A/B testing methodologies, causal inference, and predictive modeling
• Ability to translate complex data insights into strategic business recommendations
• Familiarity with BI tools (e.g., Tableau, Looker) and data visualization best practices
• Strong problem-solving skills and the ability to work in a fast-paced, cross-functional environment

Desirable

• Our Scientists and Engineers work together to make data — and insights derived from data — a core asset across Brex. But it's more than just crunching numbers
• The Data team at Brex develops infrastructure, statistical models, and products using data
• Our work is ingrained in Brex's decision-making process, the efficiency of our operations, our risk management policies, and the unparalleled experience we provide our customers
• As a Data Scientist focused on Product Analytics, you will work closely with Product, Engineering, and Customer Success teams to understand the interactions between product engagement, customer retention, and overall customer growth
• Your work will be instrumental in shaping product decisions by uncovering insights into how customers interact with Brex’s platform, identifying opportunities to refine the product experience, optimize user workflows, and introduce impactful changes that increase long-term customer value and drive sustainable revenue growth
• Develop and apply data-driven methodologies to analyze customer behavior, retention trends, and product adoption, focusing on how product changes impact long-term customer value
• Design and implement predictive models, causal inference methods, as well as experimentation strategies to measure and optimize the effect of product changes on customer growth and engagement
• Partner with Product, Engineering, and Customer Success teams to identify key opportunities for improving customer engagement and long-term retention
• Collaborate with Data Engineering to build scalable data pipelines that support product analytics and reporting
• Clearly communicate findings and strategic recommendations to both technical and non-technical stakeholders