Top Analytics Jobs in Cincinnati, OH

Analyze consumer, shopper, market, and retailer data to uncover insights that inform business strategy, product design, pricing, media, retail, and go-to-market decisions. Conduct qualitative research, identify business drivers, communicate findings, and influence cross-functional teams including Brand Management, Finance, Sales, and R&D. The 12-week internship requires strong analytical, communication, curiosity, creativity, and collaboration skills.

Analyze multiple data sources, derive actionable consumer insights, translate complex analytical results into clear conclusions, and influence Customer and Brand teams’ business decisions. Interns collaborate across teams, solve ad hoc problems, communicate findings, and support technology-enabled analytical solutions during a 12-week internship.

Lead portfolio analytics for Amazon Credit & Payments: define problems, source and analyze data, build dashboards, measure and optimize lifecycle and campaign performance, partner cross-functionally, and coach analytics teams to drive growth, profitability, and improved customer experience.

Ensure accuracy, integrity, and compliance of master and reference data across enterprise systems. Enforce governance, validate and remediate Salesforce and other system records, perform audits/cleansing/de-duplication, support migrations and integrations, produce reports and insights, and partner with global teams to improve data processes and adoption of standards.

Uses consumer, shopper, market, and retail analytics alongside qualitative research to uncover insights, inform business strategy, evaluate advertising and promotional investments, and influence product, pricing, media, retail, and go-to-market decisions. Partners cross-functionally with Brand Management, Finance, Sales, R&D, and other teams to communicate findings, identify growth opportunities, and drive action.

Collect, analyze, and interpret complex datasets to create and maintain customer-facing Tableau reports; collaborate with customer services and development teams to scope reports and data models; investigate data accuracy issues and communicate insights to stakeholders.

Data and Analytics Consultants solve business challenges, drive data strategies, and implement solutions while collaborating across various organizational levels.

Lead consolidation and analysis of forecast and month-end results for PBM business segments. Prepare executive summaries, coordinate impact analyses and audits, collaborate with business and technical teams to implement data-driven solutions, and support management decision-making with large PBM datasets and executive presentations.

Lead analytics and data science initiatives to drive measurable business outcomes across various functions, including Underwriting and Claims. Oversee the full analytics lifecycle, foster stakeholder engagement, and mentor junior team members.

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.

Leads commercial analytics and AI workstreams for MedTech, evaluating campaigns, customer engagement, channel performance, and sales outcomes. Develops data products, semantic models, KPI frameworks, curated datasets, and automated pipelines. Partners with Marketing, Sales, Data Science, Technology, and vendors to build and manage conversational and Agentic AI analytics solutions. Presents insights and recommendations to senior leaders, supports data-driven decisions, monitors AI performance, and maintains trusted commercial data foundations.

Design, build, test, deploy, and support scalable data analytics, BI, and reporting solutions using Azure, SQL Server, Power BI, OLAP and ETL tools. Own end-to-end delivery in a small Agile team, perform data modeling, performance tuning, production support, and apply data governance and AI-enabled tools to improve automation and insights.

The Senior Analytics Engineer will design and implement scalable data solutions for Finance Analytics, reconcile data accuracy, and collaborate across teams to enhance financial datasets and reporting workflows.

Lead advanced analytics for countrywide insurance product programs: build dashboards and monitoring frameworks, conduct deep-dive analyses and predictive modeling, identify systemic process and data gaps, partner with product and cross-functional teams, and influence strategic decisions to improve growth, retention, and profitability.

Lead the design and operation of automated compliance monitoring for consumer lending: translate regulations into rule-based data checks, own exam and audit data requests, triage exceptions, drive automation, steward compliance data, and provide technical mentorship to a supporting analyst. Produce audit-ready, reproducible evidence for regulators, bank partners, auditors, and senior leadership.

Build and maintain Salesforce CRM Analytics datasets, dashboards, and dataflows to support revenue reporting, forecasting, and planning. Design analytical models, ensure data quality and governance, integrate cross-functional data, troubleshoot CRMA performance, and enable stakeholders with reusable analytics and clear insights.

The Data Product Analyst designs and manages data products for insurance domains, ensuring they meet analytical and compliance standards while collaborating with cross-functional teams.

Provide geospatial and market intelligence to support leasing, marketing, investments, and development. Maintain geospatial datasets and trade areas, perform location-based analyses integrating internal and third-party data, build maps/dashboards/reports, and apply AI-enabled tools and automation to improve research, reporting, and decision support across the organization.

Provide insights and recommendations to improve end-to-end purchase customer journeys across web and app for B2C and B2B. Lead A/B testing and experimentation, ensure accurate data collection and impact measurement, build self-service reporting and visualizations, query and process data, and present findings to stakeholders and senior leadership.

The Senior Data Engineer will design, build, and support data environments, orchestrate pipelines, and implement data solutions for advanced analytics and machine learning, working closely with project teams.

The Analytics Lead oversees the data team operations, ensuring accurate analytics and reporting, leading team capabilities, and mentoring analysts to provide high-impact solutions.

Partner with sales leadership to define business requirements, design end-to-end analytics solutions (data models, semantic layers, dashboards), build scalable Power BI/Microsoft Fabric reporting, translate data into executive-ready insights, drive automation and standardization, mentor analysts, and influence business decisions with data-driven recommendations.

Lead and develop a team delivering enterprise data engineering, analytics, and governance. Oversee data pipelines, ETL/ELT, cloud platforms, integration services, and stakeholder engagement to enable data-informed decision-making across the university system.

Build, maintain, and validate production data pipelines and ETL infrastructure (BigQuery/GCS/dbt/Airflow alternatives). Ensure data observability, SLAs, and automated tests to deliver reliable datasets that support campaign decision-making and organizers. Collaborate with product and data teams across fast-paced, cycle-driven work.

Lead a small data engineering team partnering with Engagement Marketing to build scalable ETL/ELT pipelines, ensure data quality, define marketing metrics, integrate trusted data with ad platforms, and drive the data roadmap to enable measurement and growth.