Top Remote Analysis Reporting Jobs in Dayton, OH

Develop and maintain automated data pipelines, API-driven workflows, and data integrations using Python, SQL, Databricks, and data lake architectures. Improve data quality through validation, schema design, and provider data mapping across diverse sources. Build analytics-ready datasets for predictive analysis, Power BI reporting, and GIS-based access analyses. Document data flows and technical configurations, support knowledge transfer, and collaborate with analysts, product owners, contractors, and government stakeholders.

Process and analyze datasets, develop and maintain Power BI and Cognos reports and dashboards, troubleshoot data issues, collaborate with stakeholders and technical teams, and document reporting processes. The intern will support business intelligence needs while pursuing a related college degree and working full-time in summer and part-time during the school year.

Builds and maintains scalable data pipelines, ETL infrastructure, data warehouses, and analytics tools. The role assembles complex datasets, automates processes, optimizes data delivery architecture, and supports cross-functional data initiatives. Collaborates with executive, product, data, and design stakeholders to resolve technical issues and improve analytics systems. Requires proficiency in SAS, Python, Java, MATLAB, SQL, NoSQL, Hadoop, MapReduce, Hive, Presto, UNIX, and Linux, with JavaScript, R, and basic machine learning preferred.

Leads data analytics and operational transformation for the Magnetic Resonance team. Oversees exploratory analysis, predictive modeling, forecasting frameworks, metrics, visualizations, and scenario-based insights to improve delivery and installation performance. Partners with regional, segment, business, and technical stakeholders to support planning, strategic initiatives, data transparency, and continuous improvement. Travel to manufacturing or customer locations may be required.

Lead enterprise metadata strategy, standards, governance, capture, curation, validation, lineage, and lifecycle management across data products and business assets. Partner with data governance, engineering, quality, analytics, modeling, and stewardship teams to improve data trust, discoverability, reuse, and AI readiness. Drive metadata automation, catalog synchronization, certification support, issue remediation, and stakeholder communications across a complex enterprise data environment.

Owns the company’s BI platform and data strategy across clinical, operations, finance, and HR functions. Responsibilities include setting the analytics product roadmap, governing data definitions and PHI, managing platform architecture, building dbt models and dashboards, delivering healthcare quality and value-based-care analytics, deploying conversational AI, coordinating vendors and multi-team programs, and developing an analytics team. The role requires hands-on ownership of clinical data, EHR integrations, semantic modeling, governance, and executive reporting.

Builds and maintains analytical data foundations for lending, underwriting, pricing, originations, collections, and portfolio analytics. Develops reusable SQL assets, dimensional models, data marts, transformation workflows, reporting solutions, and business intelligence products using SQL, Python, dbt, Git, Snowflake, Power BI, and Sigma. Partners with technical teams, analysts, and business stakeholders to integrate data, standardize metrics, automate testing, and deliver reliable, documented, scalable analytical assets.

Build and maintain enterprise data pipelines and infrastructure supporting natural-language querying, semantic search, knowledge graphs, and GraphRAG for the SEC. Responsibilities include onboarding data sources, processing XBRL and financial filing data, managing metadata and lineage, validating data quality, monitoring pipeline health, resolving integration issues, and using AWS data services. The role also requires compliance with federal security standards and collaboration with the Data Architect.

Build and operate large-scale data pipelines, web-scraping systems, and data-collection tools for AI datasets. Maintain analytical databases, optimize queries, troubleshoot pipeline and data-quality issues, manage containerized workloads across Kubernetes and Linux infrastructure, and support CI/CD workflows. The role also involves documenting technical processes, researching improvements, and developing scalable APIs in a fully remote environment.

Conducts public health data validation, management, quality assurance, geospatial and molecular HIV analysis using SAS and R. Responsibilities include developing codebooks and data management plans, identifying discrepancies, performing duplicate and comparison procedures, generating reports, interpreting results, disseminating data, and collaborating with analysts, federal partners, jurisdictions, and community-based organizations.