Top Data & Analytics Jobs in Cincinnati, OH

Own support analytics for User Operations: build dashboards and recurring reports, track north-star metrics (cSAT, TTR, QA, escalations), instrument Zendesk, connect support to product/customer data, quantify operational costs of bugs, and measure AI-driven support performance.

Lead and scale Boulevard's data platform engineering organization to build reliable, secure, and performant data pipelines, governance, ML/AI infrastructure, and customer-facing data products. Partner with Product and Insights to deliver reporting and analytics, enforce data quality and HIPAA-compliant security standards, and drive strategic roadmap and operational excellence.

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 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.

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.

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.

Design, build, and operate scalable PostgreSQL databases and cloud-native data infrastructure. Build and maintain ETL/ELT pipelines, optimize query and server performance, ensure high availability and disaster recovery, improve observability, troubleshoot production issues, guide schema and application design, evaluate database technologies, and mentor junior engineers to support reliable, secure data-driven applications.

Partner with Marketing, Sales, Finance, Product and other teams to turn business questions into actionable analysis. Own end-to-end analytics: build datasets and dashboards (dbt, LookML), maintain metric definitions and caveats, use and curate agent tooling for trustworthy answers, and contribute small data platform and pipeline improvements.