Data Scientist

• Define and guide the Power & Energy segment data vision, structure, and standards
• Map the current-state data landscape, including systems, flows, redundancies, and gaps
• Define and maintain the future-state data architecture vision and roadmap
• Establish principles for scalable, reusable, and governed data ecosystems
• Build and maintain conceptual data models for core business entities and relationships
• Guide logical and physical data model development with engineering teams
• Apply industry-standard modeling techniques, including dimensional and data vault modeling
• Define canonical data definitions and promote reuse across domains
• Partner with the Lead Data Engineer to translate architecture into implementable solutions
• Oversee end-to-end data solution design from ingestion through consumption
• Ensure architecture decisions support performance, scalability, and extensibility
• Review and validate solution designs against architectural standards
• Build relationships with business stakeholders and cross-functional teams
• Present findings and drive alignment between technical solutions and business outcomes
• Advise on data-related decisions and trade-offs
• Identify and leverage appropriate data sources for use cases
• Enforce enterprise data standards, governance policies, and security requirements
• Promote data quality, consistency, and lineage
• Define standards for metadata management, data classification, and access controls

Lead Data Specialist

• Partner with data scientists, software engineers, and product managers to deliver customer-focused products
• Use Python, Conda, AWS, H2O, Spark, and other technologies to analyze large volumes of numeric and textual data
• Build machine learning models through design, training, evaluation, validation, and implementation
• Build a robust scoring platform and deploy models
• Create innovative analytical tools and leverage alternative data sources
• Collaborate cross-functionally with engineering and product teams
• Scale products, valuation models, and analytical capabilities
• Translate complex data science work into tangible business goals
• Research and evaluate emerging technologies and state-of-the-art methods
• Support credit decisioning, cash flow underwriting, and real-time credit analytics

Senior Associate, Data Scientist – Credit Card Innovation

• Apply and extend enterprise data governance frameworks to acquired-company integration
• Embed governance requirements into migration, integration, modernization, archival, reporting, and analytics enablement activities
• Establish a full data-estate view for each acquisition, covering structured and unstructured content
• Catalog acquired-company content by category, sensitivity, ownership, business purpose, and disposition
• Advise technology teams on migration, archival, preservation, and disposal decisions
• Assess content for regulated, privileged, personal, and client-confidential material and define handling requirements
• Identify accountable data owners and obtain documented approval for new or materially changed data use
• Manage external sharing and third-party access approval paths
• Classify data against retention requirements, establish retention periods and triggers, and coordinate defensible disposal
• Confirm and track legal and business holds
• Account for jurisdictional privacy, data residency, and statutory retention differences
• Define data quality rules, profiling, remediation, reconciliation, and quality gates
• Standardize definitions, formats, critical data elements, metadata, lineage, and ownership expectations
• Maintain data catalogs and business glossaries
• Support data consumers and manage stewardship activities
• Support adoption and rollout of governance technologies and work with IT, platforms, and vendors
• Operationalize privacy, security, classification, access, masking, retention, and disposal controls
• Monitor governance performance and produce executive-ready dashboards and reports
• Facilitate cross-functional governance sessions and support source-to-target mapping, lineage, reconciliation, issue resolution, and integration readiness
• Improve governance processes, quality controls, stewardship, metadata, automation, reporting, and delivery repeatability

Manager, Data Transformation – Governance

• Develop business strategies driving growth, profitability, and competitive success for Velocity Black
• Own the health, growth trajectory, economics, and P&L accountability of the Velocity Black business
• Lead strategic planning over a 6–12 month horizon
• Manage and develop a team of analysts; coach and mentor associates across the organization
• Develop and implement product and pricing strategies
• Lead product-level modeling and analytics
• Lead direct-to-consumer marketing efforts and strategic intent across channels
• Build targeted insights to inform new customer experiences, technology, concepts, and go-to-market strategies
• Coordinate across lines of business to sequence delivery, build business requirements, and execute product strategy
• Oversee multiple projects and programs concurrently
• Partner with Sales, Operations, Marketing, Finance, and other Capital One and Velocity Black colleagues to improve quality, volume, service, and profitability
• Drive the long-term strategy for Velocity Black within Capital One’s premium portfolio

Senior Business Manager, Velocity Black Strategy & Analytics Lead

• Build predictive models to optimize lending decisions using advanced statistical modeling and simulation techniques
• Use advanced data analytics to understand consumer risk behavior trends, their impact on the portfolio, and resulting business opportunities
• Establish key performance metrics and develop automated reporting dashboards using SQL and Python
• Design A/B testing for models and underwriting strategies, evaluate impact, and provide recommendations
• Work on real projects that move the business forward while receiving hands-on professional development

Data Science Intern

• Design, develop, deploy, and monitor machine learning models, predictive analytics solutions, and generative AI applications
• Build and maintain scalable data pipelines, data products, and curated datasets on Databricks
• Transform application, operational, and telemetry data into trusted enterprise assets
• Architect and deliver self-service analytics, interactive reporting, and conversational "chat with your data" experiences
• Write and review production-quality Python, SQL, and Spark code
• Establish best practices for software engineering, data quality, testing, model development, AI governance, and MLOps
• Own the team's technical roadmap and drive architecture decisions
• Partner with product managers, business stakeholders, engineers, architects, and technology leaders
• Prioritize opportunities, align technical solutions to business needs, and deliver measurable value
• Lead, mentor, and develop a high-performing team of data scientists, engineers, and analysts

Principal Data Scientist

• Understand, document, and analyze current-state capabilities regarding one or more Risk methods
• Leverage industry benchmarking to determine best practices and lessons learned regarding Risk framework components
• Write and revise policies, standards, procedures, and guidelines
• Develop and enhance processes, tools, templates, and job aids
• Write, contribute to, edit, and deliver presentations supporting the design, development, refinement, and use of Risk methods
• Collaborate across Operational Risk Management, Enterprise Risk Management, Compliance, Business Risk Offices, Operational Risk Sub-Steward organizations, Information Technology, Basel Program, Internal Audit, Regulator Relations, and other organizations to achieve objectives
• Manage data-adjacent risks across the Data Governance and Pricing team within Global Payment Networks, including Network Conflict Risk, External Data Sharing, SCAN Findings, Privacy, Feature and Script Governance, and Interchange Fee Prohibition Act risks

Data Scientist jobs in Illinois