Data Scientist

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.

We 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.

• Analyze customer-level financial health, including revenue consistency, margin structure, cashflow, marketing efficiency, inventory cycles, capital usage, and risk indicators

• Create customer health scores, segmentations, and heuristics that the entire company can rely on

• Identify early signs of distress, churn risk, and growth potential

• Conduct 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, etc

• Benchmark customers against peers to define “healthy” vs “unhealthy” patterns

• Partner with CS, GTM, and Capital teams to analyze behavior across segments, identify high-value opportunities, and explain customer challenges

• Build reporting and dashboards that reveal patterns in product usage, financial outcomes, and customer lifecycle journeys

• Surface actionable insights to improve activation and strengthen customer relationships

• Inform underwriting models with customer behavior and financial patterns

• Partner with Product to define metrics, craft intelligence features, and identify opportunities for automation and ML

• Enable GTM to tell more compelling customer stories grounded in data

Required

• 5+ years experience in customer analytics, data science, financial analysis, or a related quantitative field

• Strong background in statistics, machine learning, computer science, or quantitative discipline, especially with large data sets. Comfortable working with messy real-world data is a must

• Experience analyzing customer behavior, product usage, lifecycle metrics, or financial/transactional datasets

• Ability to synthesize complex data into clear insights and compelling narratives for non-technical audiences

• Familiarity with e-commerce fundamentals (conversion, CAC, LTV, margin structure, inventory cycles) or strong willingness and ability to become an expert quickly

• Comfort working cross-functionally with Product, CS, or GTM teams

Preferred

• Experience with fintech, e-commerce, lending, or D2C businesses

• Background in FP&A or consumer insights research

• Experience leading open-ended financial market research and generating useful insights

• Experience launching a public facing data visualization or DaaS product is a plus

• You love working in-person with a high-performing team

• You enjoy working in an idea-meritocratic, low-ego environment

• You are proactive and self-directed, and you excel in ambiguous, fast moving environments

• You care about delivering a polished customer experience

• Bonus: You have experience working in fintech, AI or early-stage startups