Top Senior Analytics Jobs in Nashville, TN

Own SQL and dbt-based data modeling and data quality for clinical and claims datasets. Author and refactor dbt models/tests, triage DQ alerts, design monitors, optimize SQL performance, and collaborate with Data Engineering and stakeholders to ensure trusted production datasets.

Build and scale the analytics foundation: own dbt projects and Snowflake warehouse, create trusted datasets and semantic layers for AI, build ELT pipelines from APIs, implement testing/observability and CI/CD, design reconciliation models, enable stakeholder self-service, and partner cross-functionally to drive data-driven decisions across GTM, Product, Finance, People, and Operations.

Leads enterprise operational and clinical reporting, including KPI governance, dashboard development, data quality, self-service analytics, and reporting readiness for new markets. Partners with clinical, operations, finance, quality, data engineering, and IT teams to convert business needs into actionable insights. Manages the analytics roadmap, ensures HIPAA-compliant practices, improves reporting standards and adoption, and coaches a growing analytics team.

Lead strategic revenue cycle analyses to diagnose patient billing and collections performance, quantify ROI and value, build executive-ready recommendations and playbooks, partner cross-functionally, and mentor teammates to drive scalable, data-driven improvements.

Lead architecture, systems, and roadmap for Coinbase's Compliance Reporting Data Platform. Design and build production-grade data models, pipelines, quality frameworks, validations, and certification processes. Establish data contracts, monitoring, reconciliation, and audit-ready processes. Partner with engineering and compliance stakeholders, respond to regulatory exams, and mentor engineers while shaping standards and documentation.

Serve as a strategic analytics advisor designing and implementing Adobe Analytics and CJA solutions, conducting measurement workshops and audits, building dashboards, translating insights into action, training clients, and ensuring data security and privacy compliance.

Lead and grow the Revenue Analytics team to deliver strategic sales and customer lifecycle insights. Build forecasting, pipeline, capacity, predictive models, and customer lifecycle analytics to improve revenue, retention, adoption, and expansion. Partner with GTM, Finance, Product, and Enterprise Data to create executive reporting, data governance, AI-enabled self-serve datasets, and integrated analytics that drive business outcomes and support a shift to consumption-based models.

Lead development of scalable, well-tested data products for Revenue: design dbt models, metrics, dashboards, governance, and AI-enable analytics. Drive technical direction, automation, quality, and mentor cross-functional partners to deliver trusted reporting and self-service analytics.

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.

Leads an analytics team delivering actionable insights, forecasting, statistical analysis, reporting automation, visualization, and client-focused tools. Oversees analysts, develops team talent, enhances databases and analytical processes, manages client and vendor relationships, and presents recommendations to executives. The role requires advanced Excel, business intelligence, data mining, statistical modeling, cross-functional collaboration, and strategic leadership, with health insurance analytics experience preferred.

As a Data and Analytics Consultant, you will support clients by leveraging data to drive strategic initiatives, lead modernization efforts and build collaborative teams.

Leads analytics delivery across multiple clients, combining marketing data to evaluate performance, optimize investments, and inform growth decisions. Designs and implements advanced measurement approaches including attribution, incrementality testing, experimentation, and full-funnel measurement. Develops measurement frameworks, communicates insights to clients and senior stakeholders, partners with technical and marketing teams, supports new business, and mentors junior analysts.

Owner of the analytics foundation: design and maintain BigQuery/dbt models, pipelines, and Looker Studio reporting; build AI workflows and web apps on GCP; integrate marketing, e-commerce, and fulfillment data; ensure GCP ops, security, and reliability; use AI-assisted tools daily and collaborate with business and client stakeholders.

Lead a team delivering marketing analytics and consulting services, performing marketing mix modeling, attribution, digital analytics, pricing/promotions, and demand forecasting; provide analyses, recommendations, and client-facing presentations while traveling extensively.

Lead product analytics: build and maintain dbt models and Looker dashboards, define KPIs, analyze funnel and user journeys, design and evaluate A/B tests, size roadmap impact, and deliver partner and ad-hoc insights to inform product and executive decisions.

Lead development and scaling of financial analytics: build data models, dashboards, and reporting; translate financial data into executive insights; embed predictive analytics; partner with Finance, IT, and business units to improve data quality, governance, forecasting, and automation.

Lead the design and implementation of scalable data models, transformation pipelines, semantic layers, and analytics engineering solutions. Drive dbt best practices, testing, CI/CD, data governance, quality improvements, performance optimization, and technical standards. Collaborate with analysts, engineers, stakeholders, and clients to translate business requirements into reliable data architectures. Mentor peers, lead technical implementations and delivery workstreams, reduce technical debt, and contribute to shared tooling and frameworks.

Lead end-to-end analytical initiatives on partner enrollment funnels, ensure data quality, build reporting pipelines with BI/engineering, use AI-assisted tools to accelerate analysis, translate insights into strategic recommendations for leadership, and coach growing analytics team members.

Leads and scales a global data engineering and analytics team while remaining hands-on with architecture, pipelines, data quality, dimensional modeling, dashboards, reporting, and customer-facing deliverables. Owns the analytical data platform supporting clinical, operational, product, financial, and customer data. Partners with cross-functional stakeholders, investigates complex data issues, improves platform reliability and security, and mentors engineers.

Own client-facing analytics and attribution: establish baselines, implement tracking and lead-to-sale matching, run holdout and lift experiments, quantify cost avoidance, build cross-client benchmarks, and translate findings into clear ROI narratives that inform pricing, product, and renewal conversations.

Builds and maintains analytical data foundations for lending, underwriting, pricing, originations, collections, and portfolio analytics. Develops reusable SQL assets, dimensional models, data marts, transformation workflows, reporting solutions, and business intelligence products using SQL, Python, dbt, Git, Snowflake, Power BI, and Sigma. Partners with technical teams, analysts, and business stakeholders to integrate data, standardize metrics, automate testing, and deliver reliable, documented, scalable analytical assets.

Lead strategic insights and market research projects for B2B clients, translating quantitative survey and statistical analysis into actionable recommendations. Manage client engagements, design surveys using methodologies such as conjoint and MaxDiff, present findings to nontechnical stakeholders, develop commercial offers, and coach Associates. The role supports marketing, product development, and strategic planning while helping build NewtonX’s professional services capabilities.

Lead infrastructure analytics for compute, storage, and networking: design scalable data pipelines, define core metrics, build dashboards and APIs, ensure data quality and governance, drive instrumentation fixes, and advise executives on capacity, utilization, and readiness.

Leads the analytics products team and oversees the development, integrity, maintenance, and delivery of dashboards, reports, models, extracts, and routine data deliverables. Delegates work while remaining hands-on enough to ensure product quality and technology alignment. Partners across revenue cycle business services and applies analytics, project management, change management, business transformation, facilitation, and process improvement practices.

Own enterprise analytics audits, implementations, data quality, attribution, segmentation, SQL analysis, BI dashboards, experimentation measurement, and client reporting. Serve as the senior analytics partner for major accounts, present insights to executives, train client and internal teams, and help define analytics and experimentation services. The role requires hands-on Adobe expertise, autonomous prioritization, technical collaboration, and the ability to connect organic and AI search performance to pipeline and revenue.