Principal Data Scientist, Payments Intelligence
About The Position
WEX is seeking an entrepreneurial Principal Data Scientist with deep payments expertise to define and build intelligent payment products. The role combines hands-on data science, machine learning, payments-domain knowledge, and product judgment to identify valuable opportunities in corporate payments data and turn them into production-ready intelligence. It is a hands-on, end-to-end individual-contributor role with near-greenfield ownership, focused on revenue growth and measurable business value rather than traditional analytics or reporting. Initial areas of exploration include BIN routing optimization, supplier onboarding, customer acquisition, and connecting suppliers that already accept card payments with WEX customers. The role will also help establish a trusted intelligence foundation for future AI agents and agentic payment experiences. The successful candidate will independently develop a portfolio of high-value opportunities, validate them with evidence, and partner with Product and Engineering to scale the resulting capabilities. As the portfolio grows, there may be an opportunity to build a supporting team, though direct people management is not part of the initial role; continued individual-contributor growth is also supported.
Requirements
- At least 10 years of relevant experience in data science or a related quantitative discipline, including hands-on experience building production machine-learning, predictive, optimization, or decisioning solutions.
- Deep subject-matter expertise in payments, credit cards, payment transactions, or payment infrastructure.
- Experience in several relevant areas, such as authorization, acceptance, interchange, BINs, merchant behavior, payment routing, fraud and risk, transaction economics, settlement, or payment-network dynamics.
- Strong Python and SQL skills and experience working with large-scale transactional datasets.
- Ability to work across exploratory analysis, feature engineering, modeling, experimentation, and productionization.
- Ability to interpret why patterns occurred in payment data and identify business actions that could be taken.
- Entrepreneurial, self-directed approach to identifying opportunities, exploring data, testing hypotheses, prototyping solutions, and developing business cases without a fully defined roadmap.
- Strong product judgment to distinguish technically interesting work from work that creates measurable business value.
- Ability to work with Product, Engineering, Commercial, Risk, and business leaders, and communicate clearly and succinctly with director- and VP-level stakeholders.
- Customer empathy, proactive collaboration, willingness to share learnings, accountability, and ability to constructively challenge existing approaches.
- Established technical leadership and a collaborative approach to mentoring, along with openness to learning from peers.
Nice To Haves
- Advanced degree (master’s degree or above) in Data Science, Statistics, Applied Mathematics, Computer Science, Operations Research, Economics, or another quantitative discipline; equivalent depth demonstrated through experience may be considered case by case.
- Experience with R and modern data platforms such as Snowflake or Databricks. Python and SQL are required; SAS alone is not sufficient.
- Experience at a major card network, card company, payment processor, transaction-focused fintech, or financial institution.
- Curiosity about GenAI and agentic systems and interest in designing intelligence that AI agents can ultimately consume.
Responsibilities
- Discover high-value payment opportunities using payments expertise, exploratory data science, and machine learning.
- Use corporate payments data to identify opportunities for revenue growth, improved payment economics, supplier onboarding, and customer acquisition; identify additional data that could enable further analysis.
- Build intelligent payment data products that provide predictions, recommendations, optimization, or decisioning beyond dashboards.
- Develop models and signals concerning merchant and supplier behavior, payment acceptance, authorization performance, BIN and interchange optimization, payment routing, fraud and risk, and payment economics.
- Create connected intelligence across customers, suppliers, merchants, transactions, payment methods, networks, and other payment entities.
- Identify patterns in large-scale transaction data that can improve acceptance, payment performance, revenue, and margin; form hypotheses and validate value through rigorous analysis.
- Prototype with Python, SQL, machine learning, and modern data platforms to demonstrate value before scaling solutions.
- Partner with Product and Engineering to productionize models, signals, and decisioning capabilities.
- Design experimentation and measurement frameworks to demonstrate the incremental business value of models and recommendations.
- Help define the semantic and contextual intelligence needed for future payments AI agents and agentic experiences.
- Advise Payments leadership and proactively identify opportunities rather than waiting for fully defined requirements.
- Mentor data analysts and collaborate with data scientists across the organization, sharing practices and raising technical and data-science standards.
Benefits
- Health insurance
- Dental insurance
- Vision insurance
- Retirement savings plan
- Paid time off
- Health savings account
- Flexible spending accounts
- Life insurance
- Disability insurance
- Tuition reimbursement
- Quarterly or annual bonus eligibility for non-sales roles, subject to role and applicable plan
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What This Job Offers
Job Type
Full-time
Career Level
Principal
Education Level
No Education Listed
