Top Data & Analytics Jobs in Cleveland, OH

The Data Engineer I at Storable supports the design and maintenance of data pipelines, works with ETL processes, optimizes workflows, and collaborates with various teams to enhance data accessibility and reliability.

Analyze market and live data to set dynamic ticket prices using Uptick, build strategic pricing recommendations, communicate with clients about strategy and performance, and collaborate with BI and engineering to improve product performance.

As a Director in the Data & Analytics team, you will lead client engagements, manage projects, develop strategies, create proposals, and mentor team members in data-driven initiatives.

As a Technical Solutions Manager, you'll onboard Enterprise customers onto Medallion's platform, focusing on data migration, integration, and automation for enhanced operational efficiency.

Analyze player behavior and drive product innovation through data-driven insights. Collaborate with teams to design and evaluate experiments, maintaining data quality and delivering meaningful insights.

Implement and maintain ETL processes to ingest and transform hospital data into Meduit platforms. Build data models, ensure data integrity, document and track tasks in Jira, collaborate with cross-functional teams, support revenue-cycle data implementations, and mentor team members on best practices.

As a Credit Risk Senior Analyst at Marqeta, you'll lead underwriting strategies, refine credit policies, conduct risk analyses, and present findings to senior management.

Lead data strategy at Alpha, oversee data functions, build robust data systems, drive product decisions using data insights, and mentor a data team.

Lead BI developer owning end-to-end reporting for marketing verticals. Build and standardize dashboards, model complex/third-party data (LookML), partner with Yield, Paid Media, and Account Management to deliver actionable analyses that optimize campaign performance, conversion, and revenue.

Lead the technical roadmap and hands-on development of a scalable data platform, build analytics and data access solutions, ensure data quality/governance/observability, mentor and grow a team of data engineers, collaborate cross-functionally, and evaluate new big-data technologies.