Top Analysis Reporting Jobs in Ogden, UT

Lead statistical analysis for clinical studies in oncology and cardiology, provide project leadership, and mentor junior biostatisticians while ensuring regulatory compliance.

Manage analytical service operations by overseeing a team, designing software for data mining, developing statistical models, and generating insights for marketing outcomes. Provide training and mentorship to direct reports.

Develops and maintains data-driven reporting solutions and client-facing presentation decks. Translates business and clinical reporting needs into requirements, collaborates with technical and data teams, builds reusable templates, analyzes complex healthcare metrics, validates outputs, and manages solutions through design, testing, implementation, and maintenance. Provides consultative support, presents findings to stakeholders, mentors colleagues, and uses databases, statistical tools, and reporting applications to support business decisions.

Designs, develops, and supports scalable GCP data pipelines, ETL/ELT workflows, database integrations, and data warehousing solutions. Uses BigQuery, Spanner, Dataflow, Informatica, and enterprise databases to enable analytics and applications. Responsibilities include performance tuning, monitoring GCP infrastructure, troubleshooting data quality and pipeline issues, scheduling jobs with Control-M, documenting technical procedures, and collaborating with engineers and architects in Agile environments.

Conducts research, collects and analyzes data, develops data-gathering methods, and prepares reports with tables and charts. Cleans, validates, curates, and produces production-ready data from multiple sources; supports testing, performance metrics, issue resolution, and process improvement for Air Force maintenance systems. The role requires strong analytical and problem-solving skills, advanced Microsoft Office capabilities, and preferably experience with MABSM and MRO processes.

Leads business intelligence, reporting, data modeling, and ITSM analytics for a federal IT operations contract. Analyzes CMDB, configuration, change, incident, SLA, cybersecurity, and compliance data; develops dashboards and predictive insights; supports audits, RMF activities, program reviews, and modernization planning. Coordinates with technical teams and government stakeholders to ensure accurate, traceable, and auditable analytics products.

Build and maintain production batch and streaming data pipelines, reusable ingestion and transformation components, and shared engineering patterns. Collaborate with platform and domain teams to translate requirements into secure, performant, testable, and observable pipelines. Integrate data quality, governance, monitoring, orchestration, incident response, and CI/CD practices while supporting documentation and enablement for common data engineering capabilities.

Build scalable Python backend services, data pipelines, and analytics platforms supporting fraud attribute development, machine learning model development, deployment, and monitoring. Design maintainable production systems, implement CI/CD and infrastructure as code, manage AWS and on-premises environments, improve reliability and security, troubleshoot pipelines, and process large datasets for analytics and visualization.

The Manager, R&D Data Modeler designs and governs conceptual, logical, and physical data models for R&D analytics and digital initiatives. Responsibilities include source-to-target mapping, schema optimization, data integration, metadata and naming standards, FAIR and GxP governance, model versioning, architecture workshops, platform implementation consulting, and mentoring junior modelers. The role supports scalable, interoperable data ecosystems for analytics and AI workloads across data warehouses and cloud data lakes.

Build and own AAG’s consolidated data warehouse, including production-grade infrastructure, ELT pipelines, dimensional models, and reporting layers. Integrate data from ERP, CRM, and manufacturing systems into Databricks on Azure, maintain reliable data flows, and support business decision-making across the organization. Collaborate with leadership to translate requirements into code, while managing system development, maintenance, documentation, and continuous improvement.