Principal Data Scientist, Payments Intelligence

Role overview Find ways to improve payment economics and grow revenue by turning large-scale transaction data into predictive models, recommendations, and decisioning capabilities. This is a hands-on, senior individual contributor role with substantial ownership: you’ll investigate open-ended opportunities, validate their value, and work with product and engineering teams to bring useful solutions into production.

Responsibilities - Explore corporate payment data to identify opportunities in routing, interchange, supplier onboarding, customer acquisition, acceptance, and payment performance. - Form hypotheses about transaction patterns and use rigorous analysis to test their potential business impact. - Build models and signals for merchant and supplier behavior, authorization, fraud and risk, payment routing, and transaction economics. - Prototype with Python, SQL, machine learning, and data platforms, then partner with product and engineering to productionize successful work. - Design experiments and measurement approaches to assess the incremental value of models and recommendations. - Advise business leaders on data-backed opportunities, mentor analysts, and help shape intelligence that may support future AI-driven payment experiences.

Requirements - At least ten years in data science or a related quantitative field, including hands-on delivery of production machine learning, predictive, optimization, or decisioning solutions. - Deep expertise in payments, card transactions, or payment infrastructure, with experience in areas such as authorization, acceptance, interchange, routing, fraud, settlement, or network dynamics. - Strong Python and SQL skills, with experience analyzing large transactional datasets. - Ability to work across exploration, feature engineering, modeling, experimentation, and production delivery. - Independent, entrepreneurial approach to identifying problems, testing ideas, and building a case for measurable business value. - Strong product judgment and ability to collaborate with product and engineering partners; experience mentoring or guiding data science peers.

Nice to have - Advanced degree in a quantitative discipline, or equivalent depth through experience. - Experience with R, Snowflake, or Databricks, or work at a card network, processor, fintech, or financial institution. - Interest in generative AI and agentic systems.

Benefits and work setup - Listed base pay range: $215,000–$243,800. Benefits include health, dental, and vision coverage, retirement savings, paid time off, insurance options, and tuition reimbursement.