Top Analytics Jobs in Cleveland, OH

The Senior Analyst, Revenue Operations is responsible for delivering analytical insights, enhancing forecasting accuracy, and optimizing revenue processes while collaborating with various departments.

The Digital Analytics Analyst will develop data strategies, implement analytics tools, and translate complex data into actionable insights for business impact.

Own and improve the dbt transformation layer, semantic layer, data observability, and pipeline orchestration while migrating the platform to AWS. Ensure data quality and governance to support clinical AI, collaborate with clinical, operations, and finance stakeholders, and audit, document, and fix existing data pipelines.

Lead individual-contributor who builds self-service analytics, metrics, experiments and scenario simulators to detect and mitigate fraud and safety risks. Partners with product, engineering, legal and ops to operationalize metrics, run causal analyses, and support audits, incident response, and executive reporting.

Owner of data platform modernization: design and migrate legacy systems to Kimball-style dimensional models and star schemas; build reliable production data pipelines; enforce data hygiene and validation; champion dbt best practices; mentor junior engineers; collaborate with analysts and stakeholders to ensure scalable, well-documented data models and platform observability.

Lead web analytics strategy and implementation: define measurement, maintain data pipelines, support 1P data integrations, troubleshoot tagging/pixel/API issues, create documentation and playbooks, translate analytics for stakeholders, and drive continuous improvement and AI-assisted automation.

Lead enterprise analytics strategy and roadmap, consolidate analytics teams, deliver data products and governance, scale advanced analytics and MLOps, partner with IT and business leaders to drive data-driven decision-making and measurable financial impact.

Design, build, and support SAP Analytics Cloud dashboards, planning models, and executive reporting. Integrate SAC with SAP and non‑SAP sources, develop KPIs and forecasting models, run testing and UAT, troubleshoot issues, and support production deployments and stakeholder workshops to deliver actionable analytics for FP&A and operational teams.

Client-facing Analytics Manager who architects large-scale digital analytics (GA4/Adobe), audits implementations, builds measurement frameworks, and leads GEO (Generative Engine Optimization) test & learn programs. Uses AI tools (Claude) to automate workflows, mentor teammates, manage projects, and translate data into strategic client recommendations.

Drive marketing performance measurement and attribution by building dashboards, standardizing campaign tracking across HubSpot and Salesforce, running funnel and cohort analyses, ensuring data integrity, and delivering executive reporting to connect marketing activity to pipeline and revenue.

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.

Build and maintain scalable Python-based data pipelines and backend services for analytics and ML workflows. Design software systems, support analytics/model training and deployment platforms, implement CI/CD and IaC, manage AWS/on-prem environments, monitor and improve pipeline reliability, and evaluate new AI technologies to increase platform efficiency.

Analyze business performance, provide insights, improve processes, participate in continuous improvement projects, and collaborate with cross-functional teams.

Lead the analytics team for the third-party agent business, driving business strategy, product analytics, and AI-powered insights while fostering cross-functional partnerships.

Lead global partner analytics and planning for partner GTM motions. Build dashboards, business models, AI-enabled workflows, and executive reports to support partner planning, incentives, coverage, performance management, and cross-functional decision-making across hyperscalers, ISVs, marketplaces, and reseller channels.

Lead Southern California risk, actuarial, and analytics strategy for employee benefits. Serve as market-facing advisor, drive client retention and growth, oversee advanced modeling (funding, stop-loss, forecasting), lead analytics team, scale delivery, and partner with national centers of excellence to align tools and execution.

Lead a team to analyze sales data, build and maintain Power BI and Excel reporting, leverage AI and automation for pipeline and lead scoring, align cross-functional GTM strategies, ensure data quality, and deliver actionable, executive-ready insights to drive sales performance and quota attainment.

Lead BI developer who owns reporting infrastructure end-to-end: SQL-based data extraction from messy sources, LookML/BI model development, dashboard standardization, stakeholder partnership, and performance marketing optimization to drive actionable insights and business outcomes.

Lead design and implementation of tracking with GTM, analyze user behavior in GA4, build BigQuery queries and dashboards, define KPIs with cross-functional teams, troubleshoot tagging/data issues, and perform deep-dive conversion and journey analyses to optimize web and mobile performance.

The Director of Product Analytics leads the product analytics strategy, develops a team of analysts, drives insights for product decisions, and oversees experimentation across products to enhance growth outcomes.

The Manager of Analytics oversees a team to deliver impactful analytics and insights, supports business decisions, and integrates AI applications in analytics. They also manage testing portfolios and develop actionable insights for marketing strategies.

The Senior Consultant will lead the design and implementation of data solutions using Microsoft Fabric, Power BI, and Databricks to enhance analytics capabilities for clients. They will engage with stakeholders to define data strategies and deliver high-quality consulting services across multiple projects.

Build and own the quality analytics data layer: design and maintain dbt models, data marts, and Python-driven analyses. Define and standardize quality metrics, run experiments and A/B tests, support decision-making with dashboards and reports, automate recurring reporting, and partner with Quality and Engineering to ensure reliable, documented analytics.