Top Remote Analysis Reporting Jobs in Nashville, TN

Build and maintain GTM and pipeline analytics, own forecasting and pipeline-quality metrics, execute recurring revenue operating cadences, maintain SQL queries and BI views against Salesforce/Redshift, support systems rollouts, and produce ad hoc analyses to inform leadership decisions.

Lead the architecture and development of CareDx's enterprise BI ecosystem. Own Power BI modeling, DAX optimization, governance (RLS, deployment pipelines), and self-service enablement. Collaborate with data engineering to build scalable Databricks/Delta Lake/PySpark pipelines, leverage Microsoft Fabric and Lakehouse architecture, mentor BI developers, translate business needs into analytics solutions, and drive BI performance and reliability.

Lead marketing measurement: own attribution, incrementality testing, and media mix modeling. Design and analyze experiments, build repeatable templates and self-serve analytics, translate results into budget and growth recommendations, ensure data integrity, and embed AI tools into analysis workflows to measure pipeline and revenue impact.

Lead advanced analytics and predictive modeling for readiness-based spares and sustainment decisions. Translate business problems into analytical frameworks, build predictive/diagnostic models, document data pipelines, mentor junior analysts, and collaborate with engineering and program stakeholders to support Navy and Department of War programs.

Partner with GTM leaders to turn large datasets into actionable insight, build dashboards and forecasting models, analyze pipeline/retention/productivity, and implement automation and AI-enabled workflows to improve revenue performance and GTM operations.

The Business Intelligence Analyst analyzes complex data for finance teams, develops reports and dashboards, and enhances financial reporting solutions. They collaborate with teams to ensure reporting accuracy and alignment with business needs.

Design, build, and optimize scalable batch and streaming data pipelines. Model and process structured and unstructured data, ensure production reliability and observability, apply ML techniques for insight extraction, and drive data strategy while adopting modern tooling and IaC practices.

Design and analyze experiments, measure campaign incrementality, identify customer segments and engagement opportunities, validate tracking and anomalies, surface actionable insights, and build scalable measurement infrastructure with cross-functional partners.

Build and maintain revenue and customer-lifecycle reporting, author complex BigQuery SQL, develop segmentation and clustering models in BigQuery ML, perform entity resolution and data quality reconciliation, migrate and maintain Tableau dashboards, and deliver ad-hoc and recurring analyses to support Sales, Revenue, and cross-functional teams.

Build and own data platform infrastructure and scalable pipelines (ingestion, orchestration, transformation, delivery). Define governance, observability, and AI-first architecture. Optimize performance, ensure data quality, mentor engineers, and integrate AI-assisted tooling.