Top Data & Analytics Jobs in Provo, UT

Own end-to-end data pipelines for multiple clients: extract, clean, transform, model and visualize data. Build dashboards and automated workflows, apply AI where useful, and present actionable insights to non-technical stakeholders.

Lead analytics and data science initiatives to drive measurable business outcomes across various functions, including Underwriting and Claims. Oversee the full analytics lifecycle, foster stakeholder engagement, and mentor junior team members.

The DMS Data Engineer is responsible for analyzing raw data, building data systems and pipelines, conducting complex data analyses, and collaborating on projects to enhance data quality and reliability.

As a Senior Staff Decision Scientist, you will optimize payment decisioning strategies, analyze risk data, and collaborate to improve platform performance and user experience.

Lead and expand the company's BI and analytics capabilities: set data strategy with senior leadership, manage analytics pipeline and BI stack, implement data governance, mentor and grow BI and data engineering teams, partner cross-functionally to drive data-informed decisions, and manage vendors and processes for scalability.

Lead a high-impact analytics function partnering with clinical and business leaders to apply advanced analytics, modeling, and BI to improve participant outcomes, operations, and financial performance. Manage and mentor analysts, design analyses and models, build stakeholder relationships, and communicate actionable insights to influence enterprise strategy.

Lead design and delivery of Workday reporting and analytics for AMS clients: build advanced/matrix/trending/composite reports, dashboards, Discovery Boards, Worksheets, and complex calculated fields; gather requirements, optimize reports, mentor junior consultants, and provide Workday best-practice guidance.

Perform part-time quality audits and evaluations of task outputs, define and refine quality benchmarks and scoring rubrics, analyze audit results to produce actionable insights and reports, and recommend process improvements to raise output quality.

Restructure and maintain Airtable relational architecture for fertility industry data, implement automations and integrations (Zapier, Softr), enforce data governance and permissions, build dashboards and reports, execute data acquisition and enrichment to scale the database, conduct audits, document SOPs, and support onboarding and system monitoring.

Design and deliver Databricks-centric data architectures, lead pre-sales and billable engagements, build end-to-end data engineering pipelines for AI/ML and BI, mentor teams, ensure data governance/security/quality, and resolve data system issues while producing solution documentation and presentations.