Top Remote Analysis Reporting Jobs in Dayton, OH

Build and maintain scalable data solutions in Palantir Foundry, including ontologies, data assets, pipelines, workflows, analytics, and AI/ML applications. Translate stakeholder requirements into governed, secure, and maintainable solutions; troubleshoot platform issues; support data governance and cloud modernization; and create documentation, training, and user support resources for FAA platform users.

Design, build, and maintain operational dashboards and SQL-based data models. Translate stakeholder questions into queries, validate data quality, migrate reporting to Databricks/dbt, document analytics, and support metric governance to deliver trusted operational insights.

Supports Tier 1 help desk requests, reporting, data validation, documentation, testing, and process improvements. The role assists with automations, maintains Teams knowledge content, and collaborates with senior analysts and developers while learning Power BI, Power Apps, Azure, and ARES capabilities. Responsibilities include identifying workflow inefficiencies, following up on assigned tasks, escalating issues, and supporting the transition from BusinessObjects to ARES.

Analyzes retailer, marketplace, syndicated, and household panel data to identify customer and category growth opportunities for Target’s Self Care business. Develops assortment, pricing, promotion, competitive, seasonal, and omni-channel recommendations for online and in-store growth. Presents insights, collaborates with customer development managers and internal partners, supports go-to-market initiatives, and improves analytical best practices and accuracy.

Manages the enterprise Data Governance and Analytics Center of Excellence, leading staff, governance initiatives, analytics strategy, maturity modeling, budgets, vendors, and planning. Coordinates data quality, stewardship, privacy, acquisition, and release programs while partnering with data scientists, engineers, technology governance teams, and business stakeholders. Develops executive presentations, aligns enterprise definitions and algorithms, establishes standards, and ensures analytics projects and business cases meet organizational objectives and deadlines.

Maintain mine-action information management systems, databases, data flows, and quality-control processes. Produce GIS maps, web maps, visualizations, analyses, and prioritization tools using ArcGIS and related platforms. Support mobile data collection, SQL reporting, UNMAS data transfers, staff training, and sector technical working groups. The role supervises data-collection staff and requires English and Arabic proficiency, with rotational deployment in Gaza and regional travel.

Design, build, and lead a scalable, configuration-driven data integration platform. Improve performance, automate monitoring and deployments, provide escalated support, and collaborate across product and engineering to deliver reliable, secure data integrations.

Build and own workforce capacity, forecasting, and scenario models that guide hiring, coverage, account assignments, and organizational design. Maintain executive-ready dashboards and real-time visibility into workforce supply, demand, hiring pipelines, utilization, attrition risks, and workload distribution. Partner with HR, Finance, Revenue Operations, and business leaders to translate complex workforce data into actionable decisions and ensure consistent reporting and assumptions across systems.

Serves as a strategic analytics partner to Marketing, owning funnel, attribution, ROI, account scoring, experimentation, and pipeline analytics. Builds scalable datasets, dashboards, and quality controls while connecting customer, campaign, product usage, CRM, and revenue data. Delivers executive-ready reporting, QBR insights, and recommendations that improve conversion, marketing investment effectiveness, account-based marketing, product adoption, and pipeline growth.

Design and maintain scalable ETL/ELT pipelines, analytical dashboards, and reporting tools supporting clinical, research, and operational priorities. Write production-quality Python, R, and SQL; develop data architecture; partner with data scientists to operationalize analytics; integrate AI-enabled workflow improvements; establish engineering standards; and mentor junior team members.