Top Data & Analytics Jobs

As a Manager, Data Scientist in the Application Fraud Team, you will leverage advanced technologies to build machine learning models, collaborate with cross-functional teams, and translate complex data into actionable insights for fraud prevention, enhancing customer experience at Capital One.

The Manager of Ontology and Data Modeling at Capital One is responsible for developing and maintaining enterprise ontologies to support the company’s data strategy. This role involves collaborating across teams, advocating for semantic technology, and driving data integration efforts. Primary responsibilities include managing roadmaps, delivering insights, and mentoring staff to enhance the organization's data practices.

In this role, the Principal Data Scientist collaborates with cross-functional teams to deliver AI-powered products, focusing on Natural Language Processing and large language models. Responsibilities include building and operationalizing machine learning models while innovating customer interactions with financial services through emerging technologies.

As a Distinguished Engineer at Capital One, you will lead the development of machine learning solutions for banking. You will optimize model deployment and automation, mentor internal talent, and influence engineering practices across teams. You're expected to drive innovation and articulate a bold technical vision while collaborating with various stakeholders to achieve strategic objectives.

As a Senior Machine Learning Engineer at Capital One, you'll design and implement machine learning applications using Python, Spark, and MLOPS. You'll collaborate with cross-functional teams to develop optimized ML models, monitor them in production, and apply cloud technologies for scalability. You will also ensure adherence to best practices in ML engineering, focusing on production, governance, and explainable AI.

As a Data Scientist, you will leverage your analytic and technical skills to innovate and maintain data solutions, tackle business problems, develop credit bureau data expertise, conduct deep analysis, present findings, and enhance production infrastructure.

As a Lead Machine Learning Engineer, you will design, implement, and productionize machine learning applications. You'll collaborate with cross-functional teams to build ML models, manage cloud-based architectures, and ensure high availability and performance of applications. Responsibilities include optimizing data pipelines and adhering to best practices in AI governance and deployment.