Top Remote Analysis Reporting Jobs in Dayton, OH

The Data Engineer will design and maintain scalable data pipelines, automate workflows, and enhance data governance while collaborating with cross-functional teams.

Lead end-to-end web and mobile analytics: design and implement tagging strategies, ensure data quality, build data pipelines and dashboards, analyze user behavior, and provide actionable insights to Product, Marketing, and Engineering stakeholders.

The Senior Value Attainment Analyst will analyze customer data to create ROI analyses that support renewals and expansions, ensuring accurate methodologies and compelling presentations for health system leadership.

The DMS Data Engineer is responsible for analyzing raw data, building data systems and pipelines, conducting complex data analyses, and collaborating on projects to enhance data quality and reliability.

The Technical Project Manager ensures data quality across clinical and claims datasets, validating and reconciling data while partnering cross-functionally. Responsibilities include data analysis, maintenance, and supporting integrations with engineering.

The Director of Analytics and Performance will manage campaign analytics, provide insights and strategies for healthcare clients, and collaborate with internal teams and external agencies.

The Data Architect will design scalable data models, transform raw data into actionable insights, and deploy analytics solutions for healthcare providers, with a strong emphasis on SQL proficiency and cloud technologies.

The Monetization Analyst will enhance team performance, drive efficiency across monetization, support, and online reputation, and implement AI-driven automation solutions.

The GIS Coordinator designs and maintains spatial systems for municipal clients, ensuring data integrity and integrating GIS with other government systems. Responsibilities include geospatial analytics, training users, and producing maps for decision-making.

The Senior Data Engineer will build and maintain ETL/ELT pipelines, optimize SQL queries, and collaborate on machine learning workflows, driving data engineering best practices.