Top Senior Analysis Reporting Jobs in Dayton, OH

Develop and implement commercial data acquisition and governance frameworks. Govern data standards, policies, cataloging, quality, lineage, privacy, and compliance. Evaluate and onboard external data sources, negotiate vendor agreements, and manage third-party data relationships. Lead governance platform deployment, training, change management, KPI development, reporting, and continuous improvement while coordinating Commercial Operations, Analytics, IT, and external partners.

Build and maintain production-grade data pipelines and ELT processes using Python, SQL, Airflow, and dbt within AWS. Design optimized schemas in PostgreSQL and Redshift, leverage AI/LLMs to improve development, automation, testing, and data quality, and scale infrastructure for large healthcare datasets.

Provide insights and recommendations to improve end-to-end purchase customer journeys across web and app for B2C and B2B. Lead A/B testing and experimentation, ensure accurate data collection and impact measurement, build self-service reporting and visualizations, query and process data, and present findings to stakeholders and senior leadership.

The Senior Data Engineer will design, build, and support data environments, orchestrate pipelines, and implement data solutions for advanced analytics and machine learning, working closely with project teams.

The VP Global Grid Modeling will lead global data strategy, manage high-performing teams, ensure quality datasets, and engage with customers for insights in energy markets.

Client-facing BI consultant responsible for end-to-end delivery of TARGIT-based analytics: requirements gathering, prototyping, backend work, dashboards, training, deployment, optimization, and customer engagement.

Design, build, and maintain Keboola-based data pipelines integrating multiple business systems to deliver accurate, scalable data for supply chain, logistics, and transportation analytics; collaborate with analysts and engineers; support documentation, governance, and pipeline automation.

Lead research on the macroeconomics of AI by authoring flagship reports, building quantitative forecasting models, integrating bottom-up semiconductor and datacenter data into macro estimates, developing LLM-driven research pipelines, performing econometric analysis, and communicating findings to investors, policymakers, and the public.

Lead and develop a team delivering enterprise data engineering, analytics, and governance. Oversee data pipelines, ETL/ELT, cloud platforms, integration services, and stakeholder engagement to enable data-informed decision-making across the university system.

The role involves acting as a subject matter expert in Data and AI, providing technical expertise during sales processes for Azure-based solutions, and mentoring team members to enhance client experiences.