Top Data & Analytics Jobs in Cleveland, OH

The Senior Product Analyst will automate data collection, analyze product metrics, conduct A/B tests, and support product hypothesis generation.

Develop and maintain datasets for visualization and machine learning; automate data pipelines; partner with teams to build data products.

Own end-to-end analysis of payments, chargebacks, and user lifecycle to identify drivers of net loss. Deep-dive into fraud cases, design and evaluate A/B experiments and risk-rule changes, build monitoring dashboards, partner with Risk, Payments, and Product to convert insights into mitigations, and run ad-hoc analyses of emerging loss trends.

Lead product analytics: build and maintain dbt models and Looker dashboards, define KPIs, analyze funnel and user journeys, design and evaluate A/B tests, size roadmap impact, and deliver partner and ad-hoc insights to inform product and executive decisions.

Design and implement BI solutions: build data models, automations, ETL/ELT workflows, dashboards, and ad-hoc analyses. Monitor and analyze RF/video performance using Dataminer/Qligent or similar tools. Collaborate with cross-functional teams, document requirements, and deliver actionable insights to optimize hybrid terrestrial and satellite video delivery.

Own and scale the finance and accounting data ecosystem: design and maintain BigQuery integrations, ensure data integrity and governance, build reconciliations and automated controls, develop scalable reporting and dashboards, support monthly close, forecasting, budgeting, and automate finance processes to improve visibility and efficiency.

Lead and oversee statistical programming activities, ensuring compliance with standards, managing deliverables, and implementing data strategies. Serve as an expert in statistical programming while guiding projects and improving processes.

The role involves building and scaling a Closed-Loop Design Program that enhances pre-sales engineering through data science and analytics in supply chain automation.

Lead and manage institutional research activities: collect, analyze, validate, and report quantitative and qualitative data; support program/course reviews, accreditation, dashboards, and decision-making; supervise a team and manage ad-hoc and ongoing reporting and assessment projects.

Lead design, implementation, and migration of the enterprise data warehouse from BigQuery to Databricks. Build scalable ETL/ELT pipelines, data models, governance, quality monitoring, and performance optimizations while partnering with cross-functional teams and mentoring colleagues.