Top Artificial Intelligence Data & Analytics Jobs in Nashville, TN

Lead a GTM Analytics team supporting Marketing, Sales, RevOps, and Customer Operations. Manage embedded analysts, establish trusted reporting and QA processes, review SQL and dashboards, guide funnel, campaign, sales, support, forecasting, segmentation, attribution, and experimentation analysis, and deliver executive recommendations. Partner with GTM leaders and data engineers, coach analysts, and develop self-service analytics, automation, governed dashboards, metric documentation, and AI-assisted workflows.

Owns RTB House’s performance media measurement strategy across products. Responsibilities include defining measurement taxonomies, evaluating attribution, incrementality, MMM, and MTA methodologies, managing third-party measurement partners, developing testing playbooks, piloting identity and measurement approaches, translating insights into market-facing messaging, and training commercial teams. The role requires hands-on performance media buying or oversight experience and strong ability to communicate measurement concepts, limitations, and results to technical, executive, and commercial audiences.

Own end-to-end product analytics: define questions and success metrics, run A/B tests, build dashboards and reusable SQL/Python analyses, investigate performance changes, and collaborate with Product, ML, and Data teams to inform product decisions.

Own fraud detection and mitigation for ACH payments: design controls, run investigations, analyze performance (precision/recall, financial impact), and partner with Product, Data Science, Risk ML, and Engineering to operationalize risk strategies and transition to model-driven controls.

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.

Lead and execute analytics implementations (primarily Google Analytics/GTM or equivalents), consult on technical solutions, manage client interactions, QA project work in Asana, mentor junior consultants, and deliver insights and data visualizations for clients.

Build and maintain governed Silver/Gold data models and semantic assets on Databricks. Translate stakeholder KPIs into testable, reusable transformations, apply enterprise modeling standards, enable domain self-service, ensure data sensitivity and governance, and review domain-contributed models for production readiness.

The SI Business Analyst will drive integration between business needs and technical delivery, focusing on insurance and healthcare systems. Responsibilities include capturing requirements, performing gap analysis, designing workflows, and leading cross-functional teams to optimize system performance and support digital transformation initiatives.

The Senior Analyst will support the personalization algorithm by conducting analyses, testing features, managing projects, and collaborating with teams to improve food recommendations for customers.

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.