Top Data & Analytics Jobs in Raleigh, NC

Lead enterprise data governance and data quality strategy, operating model, and roadmap. Define policies, standards, controls, and scorecards. Sponsor tools, drive accountability, chair governance forums, partner with Privacy/Security/Risk/Legal, and build culture, training, and stewardship to ensure trusted, compliant, and high-quality data across the organization.

Lead the design and implementation of enterprise-scale Knowledge Graphs and Semantic AI solutions, integrating graph intelligence and Generative AI. Manage cross-functional teams in data architecture and governance.

The Senior Analyst in AML KYC will conduct detailed customer onboarding, monitor client relationships for compliance, and update KYC records while utilizing AI tools for efficiency.

Design and maintain data quality frameworks, automate checks, validate data pipelines, and collaborate on Power BI metrics with a focus on AI-driven improvements.

The Senior Data Engineer will transform real-world data into analytics-ready datasets, build scalable pipelines, and conduct analyses to support scientific and business decisions, collaborating closely with data science teams.

Design, build, and maintain BI-ready datasets, dashboards, and monitoring tools for high-throughput lab operations. Implement process monitoring (SPC), ensure data quality and audit readiness, perform root-cause analysis, and partner with Data Science to deploy predictive models that improve throughput, quality, and compliance.

Lead design and implementation of data architecture for healthcare systems, influence stakeholders, mentor teams, ensure regulatory compliance, enable data integration and transformation, and apply AI techniques to improve healthcare operations and reporting.

Responsible for IT strategy and solutions in R&D, overseeing system integration, stakeholder collaboration, and project prioritization at Zoetis.

The Analysis Oversight Statistical Programming Lead is accountable for statistical programming deliverables, vendor performance monitoring, and team leadership within clinical studies.

Design and maintain analytics-ready data models (star schema, dimensional, relational), standardize metrics/KPIs, enable semantic models and metadata/catalog/lineage using AI-assisted tools, support data governance, quality, HIPAA compliance, and collaborate with data engineering, analytics, and business stakeholders.