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Lead a team of software engineers to develop full stack solutions and drive cloud-based projects, utilizing various programming languages and AWS services.

The role involves partnering with data scientists and engineers to develop machine learning models, evaluate model risk in fraud detection, and translate complex data insights into business goals.

The Data Scientist Manager leads a team in assessing model risks, developing machine learning models, and presenting insights, while leveraging various technologies.

As a Distinguished Software Engineer, you will design and build large-scale distributed systems, optimize machine learning platforms, and lead technical initiatives while mentoring talent.

As a Distinguished Engineer, you will lead technical innovation in AI-driven marketing systems, mentor talent, and guide architecture design. You will collaborate across teams to optimize banking solutions and influence future technology at Capital One.

Lead end-to-end technology and cyber risk management for retail bank initiatives. Conduct risk assessments (including AI and M&A integrations), track remediation, develop KRIs/metrics, drive process improvements, support audits, and partner with engineering, operations, and risk stakeholders to ensure compliance and resilience.

Lead a team delivering full-stack, cloud-based microservices and regulatory solutions. Mentor engineers, collaborate with product, experiment with new technologies, and use containers, databases, and cloud services to build scalable systems.

Perform compensation analysis for semi-annual cycles and large cross-functional projects; benchmark pay against market; model program impacts; support Workday testing, budget reporting, vendor relationships, and advance compensation market intelligence through automation and process improvements.

Lead development and evaluation of statistical and machine learning models to assess credit risk and challenge production models. Use Python, cloud, and big-data tools to analyze large numeric and textual datasets, partner with cross-functional credit risk and product teams, translate technical findings into business actions, and drive model validation, backtesting, and innovation.

Lead product design efforts combining interaction, visual, and service design. Create artifacts (journeys, prototypes, high-fidelity designs), mentor junior designers, partner cross-functionally, apply human-centered methods and data to influence product strategy, and contribute to design systems while navigating technical and regulatory constraints.