Top Remote Data & Analytics Jobs in Cleveland, OH

The GPS Business Analyst IV uses statistical analysis to support clients, conduct data reconciliations, create reports, and assist with data issues. They engage in client implementations and develop reporting packages, ensuring adherence to quality standards and communication with stakeholders.

Manage and maintain cloud-based databases, ensure reliability and efficiency, monitor performance, implement growth strategies, and develop security standards.

Seeking a Senior eDiscovery Support Analyst to maintain eDiscovery platforms, troubleshoot complex issues, and ensure exceptional client support while collaborating with various teams.

The Product Analyst will measure results and deliver insights on new AI products, identify opportunities, and guide product strategy through data analysis and visualization.

The FHIR Evangelist will shape healthcare interoperability standards, influence federal health policy, act as a trusted advisor, and build relationships in the health IT landscape. Responsibilities include participating in working groups and translating standards into actionable guidance.

The Sr. Data Engineer will design and maintain databases, develop ETL pipelines, and ensure data integrity for Hologram's IoT network, enabling insights and decision-making.

This role involves leading workforce analytics initiatives, delivering insights on headcount, compensation, and workforce planning, while utilizing AI tools and visual analytics platforms to support decision-making processes across various HR functions.

The Analyst I will contribute to healthcare data projects, supporting research design, conducting statistical analyses, and presenting findings to stakeholders.

The Advanced Analytics Manager will lead analytics initiatives, transforming complex datasets into insights, collaborating across departments to inform GTM strategy and revenue planning.

The Data QA Engineer designs and executes test plans for data pipelines and transformations, collaborates with teams to ensure data quality, and utilizes AI techniques for testing automation. They validate business metrics and facilitate cross-team communication.