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Leads global technology operations and resiliency, including incident management, change governance, operational risk and controls, security remediation, third-party risk, SRE governance, automation, executive reporting, and platform stability improvements.

Leads operational resiliency and technology governance across global engineering platforms. Oversees incident management, change control, operational risk, controls, security remediation, third-party risk, SRE governance, executive reporting, and continuous improvement. The role drives platform stability, reliability, recovery readiness, automation, standardization, and compliance across engineering and operational processes.

Lead the design and evolution of enterprise data platforms and pipelines supporting credit risk, decisioning, regulatory reporting, analytics, and AI initiatives. Architect cloud-based ETL and ELT solutions using Databricks, Spark, Delta Lake, and related technologies. Establish data quality, governance, lineage, observability, security, and compliance controls. Drive modernization, performance optimization, technical standards, cross-functional delivery, architectural decisions, mentoring, talent assessment, and strategic roadmap planning.

Leads the design, development, and modernization of enterprise data platforms and pipelines supporting credit risk, analytics, regulatory reporting, and AI initiatives. Architects cloud-based ETL/ELT and streaming solutions using Databricks, Spark, Delta Lake, and related technologies. Establishes data quality, governance, lineage, security, monitoring, and operational standards while optimizing performance and cost. Partners with cross-functional stakeholders, influences architecture and roadmap decisions, mentors engineers, and drives delivery across complex initiatives.

Leads the design and evolution of enterprise data platforms and pipelines supporting credit risk, decisioning, regulatory reporting, analytics, and AI initiatives. Architects cloud-based ETL/ELT, lakehouse, streaming, governance, and data quality solutions; modernizes legacy assets; optimizes processing; and establishes engineering standards, testing, deployment, and operational practices. Partners across risk, product, architecture, and engineering, influences technical direction, mentors engineers, supports compliance, and drives strategic roadmap execution.

Conduct analytic research for Mastercard’s Test & Learn platform, developing machine learning, causal inference, generative AI, and agentic AI solutions for complex business problems. Collaborate with product management, engineering, and business leaders to translate research into scalable products and commercial solutions. Analyze high-volume datasets, influence business decisions, manage cross-functional workstreams, communicate findings, and mentor teammates.

Conduct analytic research for Mastercard’s Test & Learn platform, developing innovative data science methods and scalable solutions for complex business problems. Collaborate with product management, engineering, and business leaders to identify customer needs, guide implementation, and influence commercial decisions using machine learning, causal inference, and generative or agentic AI. Manage cross-functional workstreams, communicate effectively with stakeholders, solve problems, and mentor teammates.

Conduct analytic research for Mastercard’s Test & Learn platform, developing novel data science methods involving machine learning, causal inference, and generative or agentic AI. Collaborate with product management, engineering, and business leaders to translate research into scalable commercial products that solve customer challenges. Influence business decisions using high-volume datasets, manage cross-functional workstreams, communicate findings, and mentor teammates.

Conducts analytic research for Mastercard’s Test & Learn platform, developing novel data science methods and scalable solutions. Applies machine learning, causal inference, and generative or agentic AI to high-volume datasets and commercial problems. Collaborates with product management, engineering, and business leaders to guide product implementation, solve customer needs, manage cross-functional workstreams, and mentor teammates.

Leads strategy, roadmap, backlog, delivery, and operational performance for AI-powered products and platform capabilities. Partners with engineering, data science, business, risk, operations, and customer success teams to define requirements, prioritize features, establish AI rules and success metrics, and deliver scalable solutions. Oversees Agile and SAFe ceremonies, release planning, APIs, integrations, data flows, platform architecture, monitoring, experimentation, and continuous optimization.