Senior Data Science Director, Dynamic Routing

Worldpay
Remote$177k – $267kPosted 6 April 2026

Job Description

Job Description Are you ready to write your next chapter? Make your mark at one of the biggest names in payments. We’re looking for a Senior Data Science Director – Dynamic Routing to join our data science team and help us unleash the potential of every business. What you’ll own as the Senior Data Science Director – Dynamic Routing The Senior Data Science Director – Dynamic Routing will lead the strategy and execution of intelligent transaction routing and pricing optimization. This position will lead a team of ~15 data scientists tasked with developing and operationalizing advanced machine learning and algorithmic solutions that optimize interchange fees, enhance transaction approval rates, and drive margin expansion for the business and its merchants. As the public-facing face of our transaction routing solutions, the Senior Director will play a crucial role in client engagements, articulating complex data science concepts in an accessible manner to explain trends and actions taken in routing. This leader will collaborate closely with business leaders to tailor strategies on a customer-by-customer basis, ensuring alignment with broader business goals. This leader will work in partnership with Product and Engineering teams to craft the future state vision for transaction routing solutions, ensuring the development of innovative products that meet evolving market demands. This role requires a deep understanding of data science methodologies and the ability to translate technical insights into strategic business actions, fostering strong relationships with clients and internal stakeholders to drive success. Strategic Leadership: • Own the data science roadmap for dynamic routing and interchange optimization across U.S. domestic, cross-border payment flows, and extension of dynamic routing globally. • Build and deploy ML/AI models that inform routing decisions based on issuer behavior, cost structures, geo/location, network rules and eligibility, and approval likelihood. • Develop scalable, low-latency algorithms integrated into real-time payment decisioning engines. • Design and validate experiments to quantify the financial impact of routing and interchange strategies (e.g., A/B tests, multi-armed bandits). • Model complex cost structures (interchange, scheme fees, FX margins) to recommend optimal routing paths for each transaction. Team & Capability Development: • Build, lead, and mentor a multidisciplinary team of ~15 data scientists and data analysts. • Mentor junior team members on best practices in modeling, experimentation, and payments domain knowledge. • Foster a culture of innovation, experimentation, and continuous learning. Cross-Functional Collaboration: • Collaborate with Product and Global Network Partnership teams to align optimization strategies with commercial agreements and market coverage. • Work closely with Finance, Product, and Worldpay’s Lines of Business to report on savings, approval uplift, and margin impact. • Communicate complex analytical concepts to non-technical stakeholders effectively. Key Areas of Focus: • Ensure models meet requirements for scalability, latency, explainability, and regulatory compliance. • Work with data governance and legal teams to ensure compliance with data privacy regulations (e.g., PCI-DSS, GDPR). • Optimize transaction paths across processors, networks (Visa, Mastercard, Regional Networks), and endpoints to maximize approval rates and minimize costs. • Use data-driven insights to steer transactions toward more favorable interchange categories or fee structures. • Model historical issuer behavior (approval decline patterns, time-of-day trends, geo-specific sensitivity). • Monitor and optimize for performance, latency, and reliability across network routes. Performance Measurement: • Define and track KPIs to measure the business and client impact of dynamic routing • Provide regular updates to executive leadership on progress, risks, and opp ... (truncated, view full listing at source)
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