Data Scientist

Data Scientist LocationNew York; TorontoEmployment TypeFull timeLocation TypeOn-siteDepartmentEngineeringCompensation$200K – $225K • Offers EquityCompensation will depend on the location and experience level.Highbeam is building the future of business banking and cash management.Our platform combines AI agents, automated financial workflows, and integrated financial products that save brands time and money.Customers have generated billions in sales and include well-known brands such as Cuts, Tushy, NYON, Sabah, Still Here, Alice Mushrooms, Original Grain, birddogs, and more.Our team includes alumni of Shopify, Square, Toast, Rippling, and McKinsey.We’ve raised $42M in equity from Acrew, FirstMark, Mayfield, and Two Sigma Ventures.About this roleWe are looking for an experienced data scientist to help build the analytical engine behind how we understand customer health, behaviors, product usage, success patterns, and risks across our portfolio of ecommerce brands.This role blends data science, customer analytics, financial analysis, and market insights to answer complex questions about how brands grow, what drives profitability, and where the market is headed. You’ll work cross-functionally with Engineering, Product, CS, GTM, and Capital to explain why customers perform the way they do, and how Highbeam can better serve them.If you love turning messy real-world data into crisp insights, building heuristics for “what good looks like,” and uncovering the drivers behind customer success, this role is for you.What you’ll doBuild a deep, data-driven understanding of each customerAnalyze customer-level financial health, including revenue consistency, margin structure, cashflow, marketing efficiency, inventory cycles, capital usage, and risk indicatorsCreate customer health scores, segmentations, and heuristics that the entire company can rely onIdentify early signs of distress, churn risk, and growth potentialBuild portfolio level intelligenceConduct quantitative research across the entire platform and market sector to understand themes in e-commerce: revenue volatility, seasonality, acquisition dynamics, category-level differences, margin pressures, discounting trends, etcBenchmark customers against peers to define “healthy” vs “unhealthy” patternsProduce insights that guide customer-facing teamsPartner with CS, GTM, and Capital teams to analyze behavior across segments, identify high-value opportunities, and explain customer challengesBuild reporting and dashboards that reveal patterns in product usage, financial outcomes, and customer lifecycle journeysSurface actionable insights to improve activation and strengthen customer relationshipsTranslate insights into strategyInform underwriting models with customer behavior and financial patternsPartner with Product to define metrics, craft intelligence features, and identify opportunities for automation and MLEnable GTM to tell more compelling customer stories grounded in dataQualificationsRequired5+ years experience in customer analytics, data science, financial analysis, or a related quantitative fieldStrong background in statistics, machine learning, computer science, or quantitative discipline, especially with large data sets. Comfortable working with messy real-world data is a mustExperience analyzing customer behavior, product usage, lifecycle metrics, or financial/transactional datasetsAbility to synthesize complex data into clear insights and compelling narratives for non-technical audiencesFamiliarity with e-commerce fundamentals (conversion, CAC, LTV, margin structure, inventory cycles) or strong willingness and ability to become an expert quicklyComfort working cross-functionally with Product, CS, or GTM teamsPreferredExperience with fintech, e-commerce, lending, or D2C businessesBackground in FP&A or consumer insights researchExperience leading open-ended financial market research and generating useful insightsExperience launching a public facing data visualization or DaaS...