Data Scientist, Financial Engineering

5+ years in a quantitative role (data science, product analytics, or experimentation) in high-growth or fintech environments

Fluency in SQL and Python, with a track record designing and interpreting A/B tests and quasi-experiments

Experience building product metrics from scratch and operationalizing them for decision-making

Excellent communication skills with PMs, engineers, risk/finance partners, and executives

Strategic instincts beyond significance tests—clear thinking about tradeoffs (conversion vs. risk vs. cost vs. user experience)

Payments, checkout, or subscription analytics experience (PSPs, bank rails, disputes/refunds, risk, e-commerce)

Background in offline incrementality methods, uplift modeling, CUPED/causal inference, or counterfactual evaluation

Experience with internationalization/local payments, FX, and pricing & packaging strategy

Comfort building operational analytics (alerting, SLIs/SLOs) and partnering closely with data engineering

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