Top Artificial Intelligence Data & Analytics Jobs in Nashville, TN

Own Silver and Gold medallion-layer modeling and semantic layer governance using dbt and SQL. Improve warehouse performance and cost, standardize BI tooling, collaborate with stakeholders to produce trusted metrics, troubleshoot data quality, and evolve analytics platform.

Lead the architecture and implementation of scalable GCP and Databricks data lakehouse platforms. Design batch and real-time pipelines, data models, governance, cataloging, security, and performance strategies. Act as a technical lead and trusted client advisor while mentoring engineers, guiding architecture decisions, conducting proofs of concept, and supporting hands-on troubleshooting and delivery.

The Facets Systems Analyst will perform development and maintenance tasks in Facets, lead a team of developers, and ensure quality outcomes through testing methodologies while maintaining compliance with healthcare standards.

Own the Databricks enterprise data warehouse and BI solution, designing data models, ETL/ELT pipelines, stored procedures, semantic layers, and governed analytics. Lead healthcare data initiatives supporting value-based care metrics such as HCC, HEDIS, Stars, utilization, MLR, and capitation. Serve as BI product owner, manage roadmap and agile delivery, enforce data quality and HIPAA-aligned controls, and lead a small team while remaining hands-on.

Leads quantitative and qualitative market research on international development, AI adoption, institutional demand, funding, procurement, competition, and commercial opportunities. Evaluates AI and data service applications, develops market assessments and strategic recommendations, manages research initiatives, prepares executive presentations, and collaborates with leadership, technical, operational, and business development teams to support market entry and growth.

Own the architecture and standards for a trustworthy BI analytics platform. Design data models, ingestion and transformation patterns, lineage, PII controls, reliability SLAs, observability, schema governance, and cost management. Partner with engineers, analysts, business leaders, Security, Legal, and Compliance; enforce testing, CI/CD, infrastructure as code, and data quality practices. Mentor data professionals and document architectural decisions.

Supports rapid A/B testing across GiveDirectly programs by designing experiments, conducting power calculations, preparing high-quality datasets, analyzing results, and translating findings into actionable recommendations. The role coordinates with Programs, Product, Research teams, and external academic partners, manages multiple concurrent experiments, prepares learning products and de-identified datasets, and helps apply evidence across country programs. The position is remote from Rwanda with regular East Africa travel.

Build and scale secure data lakehouse and warehouse infrastructure supporting analytics, machine learning, clinical AI performance monitoring, and self-service insights. Develop scalable data pipelines, models, orchestration, quality controls, and LLM-enabled analytics tools using heterogeneous clinical and EHR data. Collaborate with engineering, data science, clinical, product, and client success teams to establish trustworthy metrics and technical solutions.

Evaluates and compares chatbot responses against business requirements and quality criteria. Gathers requirements, documents functional specifications, analyzes workflows and data, creates reports and dashboards, supports testing and UAT, tracks project risks and KPIs, and presents evidence-based findings. Collaborates with technical teams and stakeholders to improve AI output quality while maintaining evaluation consistency and meeting deadlines.

Build executive-facing dashboards, scalable data models, semantic layers, and reporting datasets using dbt, Looker, and SQL. Analyze large datasets, identify trends and anomalies, manage the Looker analytics platform, resolve data quality issues, and deliver analytics initiatives across business domains. Partner with product, engineering, finance, and operations stakeholders to define metrics and reporting solutions. Mentor junior analytics engineers and improve analytics standards and documentation.