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Lead the Card Platforms and Data team, overseeing product design, collaborating with stakeholders, and driving design excellence and business outcomes. Advocate for high-leverage opportunities, foster a community of designers, and manage cross-functional collaborations to enhance customer experiences.

As a Business Analysis Manager, you will develop strategies, manage analysts, and lead product analytics to improve consumer experiences and performance metrics for the Retail Bank at Capital One.

As a Lead Data Engineer, you'll lead the design and implementation of scalable data platforms, build distributed streaming data pipelines, and collaborate on technical solutions using big data technologies and agile methodologies.

Perform operational and compliance risk activities: maintain risk/control libraries, design and test controls, create monitoring and reporting, train business partners, lead projects to improve controls and workflows, and liaise with Internal Audit and third-party risk teams.

Lead a team and portfolio building full-stack, cloud-based AML reporting solutions using distributed microservices. Design, mentor, collaborate with product managers, and deliver scalable, secure systems using modern languages, containers, orchestration, databases, and cloud services to meet regulatory requirements.

Lead analytics for enterprise marketing and messaging: build data solutions and self-service tools, mine varied data sources, develop dashboards and BI insights, ensure data quality/lineage and governance, collaborate with tech teams on security and access, and monitor data quality.

Lead strategy, product, marketing, and credit-risk analytics for premium card products. Develop pricing and product strategies, build risk models, guide go-to-market, manage projects, and mentor 1–2 analysts while partnering across IT, sales, operations, and finance.

Lead design, development, deployment, and support of large-scale AI systems (foundation model training, LLM inference, similarity search, guardrails, evaluation, observability). Optimize LLM performance and scalability, partner with cross-functional teams, and contribute technical vision and roadmap for foundational AI systems.

Lead analytical efforts to inform product, pricing, marketing, and credit risk strategies. Build and test models, perform SQL-based analysis, develop recommendations, drive implementation with cross-functional partners, and monitor results to improve profitability and customer experience.

Lead backend engineering portfolio and developer team to build cloud-based, distributed microservices and full-stack solutions. Mentor engineers, evaluate and sometimes write code, collaborate with product managers, and apply technologies like Java, Python, Node, Go, Scala, containers, and AWS to meet regulatory and customer needs.