Mastercard Offices

Develop and deploy production machine learning solutions for forecasting, recommendation, propensity modeling, fraud detection, risk modeling, and customer analytics. Define experimentation and evaluation frameworks, apply foundation-model embeddings, measure business impact, and collaborate with product, engineering, analytics, and business teams. Communicate technical findings, establish reusable modeling standards, and mentor junior data scientists.

Leads complex, cross-functional technical programs across engineering teams, regions, architectures, and vendors. Establishes program governance, delivery processes, reporting, and operating rhythms; manages risks and escalations; aligns stakeholders; communicates status to senior leadership; and builds scalable delivery and onboarding models for a growing engineering organization.

Leads complex, cross-functional technical programs from strategy through delivery. Establishes program governance, delivery processes, and operating rhythms; coordinates engineering teams, regions, vendors, and stakeholders; manages escalations, risks, dependencies, and executive communications; and drives predictable execution. The role also supports scaling engineering squads by creating repeatable delivery and onboarding models in an ambiguous, fast-growing environment.