Top Artificial Intelligence Data & Analytics Jobs in Nashville, TN

Support and improve enterprise Customer 360 and MDM capabilities through identity resolution, match/merge, survivorship, stewardship, data quality, and governance. Investigate ingestion and transformation issues using SQL and Snowflake, partner with business and technical stakeholders, automate stewardship and remediation workflows, and contribute to AI-enabled, scalable customer data solutions and operational utilities.

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.

Design and implement data warehouses, build transformation pipelines, mentor teams, and ensure data quality to facilitate informed decision-making.

Lead workforce management operations and analytics for multi-brand contact center portfolio. Manage WFM and real-time teams, forecasting, capacity planning, scheduling, intraday operations, and WFM technology optimization (Genesys, Intradiem). Drive process standardization, continuous improvement, reporting, and stakeholder partnerships to meet service levels and business objectives.

The Senior Analytics Engineer will design and implement scalable data solutions for Finance Analytics, reconcile data accuracy, and collaborate across teams to enhance financial datasets and reporting workflows.

Design and implement enterprise analytics tracking across web, mobile, and SPAs using Tealium and other TMSs. Maintain data layers and SDRs, configure tags and events, validate data integrity, collaborate with engineering teams, mentor junior staff, produce technical documentation, and support presales and thought leadership activities.

Lead KPI reporting, funnel analysis, forecasting, and business diagnostics for Enterprise Growth across Coursera + Udemy. Build unified definitions and durable self-serve reports, support experiments and inside-sales/outsourced partner evaluation, and provide analytical inputs for target setting and prioritization to drive growth and conversion improvements.

Lead and grow a data engineering team that builds and operates ingestion, transformation, orchestration, and serving layers and a self-serve analytics substrate. Own data quality, observability, cost efficiency, SLAs, and engineering practices while partnering with Data Science, BIE, Analytics, and Product to deliver reliable, reusable data products.

Lead revenue-cycle performance analyses, diagnose root causes, quantify value (ROI/collections lift), and translate findings into pragmatic, stakeholder-ready recommendations. Partner cross-functionally to scope analyses, validate data, and drive strategic workstreams that inform product roadmap and client outcomes.

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.