Top Remote Data & Analytics Jobs in Salt Lake City, UT

Own sales analytics and forecasting as the trusted source of truth for sales leadership. Build predictive and machine learning models to assess deal close likelihood and slippage, maintain Salesforce and Tableau dashboards, improve data governance, and translate complex business questions into actionable GTM recommendations. Partner with Sales, Marketing, and Finance on reporting standards, strategic planning, QBRs, and executive insights.

Lead enterprise data architecture across AWS and Databricks Lakehouse: design scalable data models, ensure governance and data quality, mentor teams, evaluate and adopt data technologies (Delta Lake, Unity Catalog), oversee large projects and deliverables, and incorporate generative AI to accelerate data modeling and delivery.

Design, maintain, and automate GTM business data models, ensure data quality and observability, build BI-as-code pipelines (CI/CD, Git), create visualizations, and partner with Sales, Marketing, Finance, and Product to enable reliable reporting, analytics, and AI capabilities.

Owns and leads commercial master data management across HCP, HCO, payer, patient, product, and organizational domains. Establishes governance frameworks, stewardship programs, data quality standards, matching and survivorship rules, and trusted golden records. Manages commercial data platforms, integrations, analytics datasets, releases, vendors, and offshore teams. Writes SQL, builds validations and data pipelines, troubleshoots integrations, supports commercial launches, and drives operational improvements across pharmaceutical commercial systems.

Analyzes claims portfolio data to identify trends, forecast losses and reserves, monitor performance, and explain variances. Develops reporting tools, dashboards, and data models while ensuring data integrity and compliance with claims policies. Partners with Claims, Finance, Actuarial, IT, Operations, and external stakeholders to support portfolio reviews, resolve reporting gaps, improve processes, and provide actionable insights for business decisions.

Support Numerator clients through ad hoc analyses, consumer-panel insights, platform guidance, reporting, and recommendations that improve sales and marketing effectiveness. The role requires understanding syndicated and household panel data, business intelligence platforms, client relationship management, presentations, and data-driven problem solving. It also involves developing expertise in Numerator solutions and sharing consumer behavior findings through industry content, forums, whitepapers, and blogs.

Organise and curate large amounts of raw material: extract key points from transcripts, collate and maintain clean spreadsheets, tag and categorise links and documents, and create findable information structures following or suggesting systems.

Performs geospatial data management, analysis, visualization, and analytical modeling for government and commercial clients. Supports hazard identification, risk assessment, and risk reduction efforts using ArcGIS and Microsoft tools. Develops web, mobile, and desktop applications; tests, deploys, documents, and maintains solutions. This non-full-time, on-call role requires frequent travel and deployment to disaster recovery sites nationwide.

Lead the architecture and scaling of Overstory’s data platform for AI-powered vegetation analysis. Design and operate large-scale geospatial and temporal data pipelines, orchestration systems, event-driven workflows, service-oriented architecture, data quality frameworks, and observability practices. Drive architectural standards, system design, scalability, reliability, and traceability while mentoring engineers and collaborating with data, ML, and product teams.

Lead Voice of Customer practice through survey and listening-program design, fielding, vendor coordination, data-quality oversight, and synthesis. Manage enterprise insights repositories, decisions journals, methodology libraries, and knowledge-transfer rituals. Maintain VoC and knowledge-management platforms, establish taxonomy and metadata standards, coach peers on research quality and documentation, and ensure organizational insights remain discoverable, credible, and reusable across staff transitions.