Top Remote Data & Analytics Jobs in Cincinnati, OH

Lead end-to-end data conversion projects: analyze, map, transform, and validate large datasets; build and run ETL/ELT processes; resolve data quality issues; coordinate cutovers and go-lives; act as primary technical customer contact; mentor junior staff; and leverage generative AI tools to streamline migrations and improve delivery.

Lead oversight of data management for assigned studies, manage external vendors, review and approve DM documentation, perform secondary UAT of EDC, implement RBQM oversight, and provide cross-functional input on protocols and study deliverables to ensure data quality and regulatory compliance.

The Sr. Underwriting Ops Associate ensures operational integrity in underwriting processes by validating data, approving quotes, monitoring performance, and partnering across teams to resolve issues.

The Data and Analytics Consultant will design, develop, and implement data reporting, visualizations, and analytics solutions for clients while assisting them in data understanding and value extraction.

The Senior Manager of Risk Analytics will lead credit risk strategies, manage portfolio performance, optimize decisioning frameworks, and drive business growth through analytics and predictive modeling.

Manage CVS Health's data partnerships and monetization strategy, source new partnerships, ensure operational success, and drive data product adoption across analytics teams.

The Data Engineer will build and maintain data platforms, deploy pipelines, monitor transformations, and collaborate with Data Scientists and DevOps.

The job involves building responsive web dashboards, advanced data visualizations, and analytics tools for unmanned aircraft systems, requiring a deep understanding of UI/UX design and data presentation.

Lead the Decision Science function, designing ML models, overseeing experimentation frameworks, and ensuring model adoption across the company, driving operational and commercial improvements.

Partner with customers and sales to design and present scalable Databricks Lakehouse architectures, build reference architectures and demos, consult on big data, ETL, and ML projects, validate integrations, and drive technical wins and adoption across accounts.