Top Remote Analysis Reporting Jobs in Dayton, OH

The Manager of RevOps/Yield analyzes patterns and data to optimize ad operations, manage vendor relationships, and oversee a remote team for revenue generation.

Build end-to-end data and analytics features: ingest and model data, build transformations and pipelines, create client-facing dashboards and interfaces, and develop LLM-powered workflows to accelerate analysis and app development. Partner with stakeholders, perform exploratory analyses, and ensure data quality, observability, and maintainability while influencing data engineering strategy.

The Senior Data Analyst will lead complex data analysis projects, mentor junior analysts, develop dashboards, and provide insights to drive strategic decisions. Responsibilities include troubleshooting data issues and communicating findings effectively.

The Staff Product Analytics Engineer will enhance product data usage across teams by owning data infrastructure, creating tools for self-service data, and ensuring data-driven decisions. Responsibilities include collaborating with various teams to improve data insights and maintain data pipelines.

Design, build, and maintain backend systems and data interactions for healthcare reporting. Develop APIs, data models, ETL pipelines, and interfaces; optimize performance, ensure data integrity and security, and support automated testing and CI/CD. Collaborate in Agile teams and reduce technical debt while enabling integrations with frontend and third-party systems.

The Staff Data Analyst will build Boulevard's product data foundation, create data-driven recommendations, develop dashboards, conduct deep analyses, and foster a data-driven culture within the organization.

Lead and build Harvey’s people analytics function: design the people data architecture, consolidate HR systems, define metrics and methodology, create dashboards and forecasting models, surface leading indicators for intervention, enable self-serve analytics, and partner with People Ops, Recruiting, Finance, and Data Engineering to drive strategic workforce decisions.

Lead design, build, and maintain scalable batch and streaming data pipelines and data warehouse models. Ensure data quality, observability, performance, and security. Own workstreams, support production incidents, and enable analysts and downstream applications.

The Data Engineer will design and maintain data pipelines, optimize cloud data warehouses, and collaborate with analytics teams while mentoring junior staff.

Manage end-to-end analytics projects, lead cross-functional teams, ensure client satisfaction, and utilize AI tools to enhance data insights.