Top Data & Analytics Jobs in Cincinnati, OH

Build and operate core data infrastructure for edge and hybrid environments, including ingestion, OT/IoT integrations, real-time streaming, data contracts, schemas, validation, lineage, observability, telemetry, and scalable query access. The role requires production ownership, reliability practices, customer integration, and collaboration across engineering and customer-facing teams. Candidates should have 6+ years of experience with production data, streaming, or integration systems and proficiency in Python and/or Go.

Analyzes claims portfolio data to identify trends, forecast losses and reserves, monitor performance, and explain variances. Develops reporting tools, dashboards, and data models while ensuring data integrity and compliance with claims policies. Partners with Claims, Finance, Actuarial, IT, Operations, and external stakeholders to support portfolio reviews, resolve reporting gaps, improve processes, and provide actionable insights for business decisions.

Support Numerator clients through ad hoc analyses, consumer-panel insights, platform guidance, reporting, and recommendations that improve sales and marketing effectiveness. The role requires understanding syndicated and household panel data, business intelligence platforms, client relationship management, presentations, and data-driven problem solving. It also involves developing expertise in Numerator solutions and sharing consumer behavior findings through industry content, forums, whitepapers, and blogs.

Own the enterprise data glossary, business definitions, governance policies, quality controls, lineage documentation, and approved sources of truth. Translate cross-functional data needs into reusable definitions and reporting, support business users, investigate data quality issues, and coordinate with product and technical teams on data model changes. The role operates independently as a senior individual contributor and drives adoption of governed data across internal and external stakeholders.

Organise and curate large amounts of raw material: extract key points from transcripts, collate and maintain clean spreadsheets, tag and categorise links and documents, and create findable information structures following or suggesting systems.

Performs geospatial data management, analysis, visualization, and analytical modeling for government and commercial clients. Supports hazard identification, risk assessment, and risk reduction efforts using ArcGIS and Microsoft tools. Develops web, mobile, and desktop applications; tests, deploys, documents, and maintains solutions. This non-full-time, on-call role requires frequent travel and deployment to disaster recovery sites nationwide.

Lead the architecture and scaling of Overstory’s data platform for AI-powered vegetation analysis. Design and operate large-scale geospatial and temporal data pipelines, orchestration systems, event-driven workflows, service-oriented architecture, data quality frameworks, and observability practices. Drive architectural standards, system design, scalability, reliability, and traceability while mentoring engineers and collaborating with data, ML, and product teams.

Lead Voice of Customer practice through survey and listening-program design, fielding, vendor coordination, data-quality oversight, and synthesis. Manage enterprise insights repositories, decisions journals, methodology libraries, and knowledge-transfer rituals. Maintain VoC and knowledge-management platforms, establish taxonomy and metadata standards, coach peers on research quality and documentation, and ensure organizational insights remain discoverable, credible, and reusable across staff transitions.

Develops business intelligence, reporting, data pipelines, dashboards, and geospatial solutions for complex real estate portfolios. Transforms and integrates data from multiple sources, builds scalable analytics products, automates reporting processes, and supports portfolio planning, occupancy strategy, workplace initiatives, and operational decision-making. Partners with stakeholders and clients to translate business needs into technical solutions, communicate insights, train users, and improve analytics adoption. The role also supports geospatial capabilities and leverages emerging AI-enabled tools.

Own and maintain data products end-to-end for sector teams, analyze large datasets, refine methodologies, automate workflows using AI and tooling, collaborate with Research, Engineering, and Product, and deliver accurate, client-facing insights and improvements.