Top Analytics Jobs in Ogden, UT

Design, build, and maintain dbt models, ELT pipelines, Looker explores and visualizations. Drive analytics strategy, data discoverability, observability, lineage, and security. Mentor engineers, collaborate cross-functionally, apply software engineering best practices, and integrate AI to scale data products and self-service BI.

Lead a team of data engineers and analysts, define the data engineering roadmap, oversee data infrastructure, ensure analytics delivery, and establish data governance standards.

Perform quantitative analysis and model development support within an economic capital team. Clean and explore large datasets, run basic diagnostics, build visualizations, and assist in validating predictive and ML models using Python/R/SAS and spreadsheet tools. Help integrate AI-generated code and agentic tools under manager supervision.

The Senior Data Engineer will design, build, and support data environments, orchestrate pipelines, and implement data solutions for advanced analytics and machine learning, working closely with project teams.

The Analytics Engineer will design, build, and maintain scalable data models, collaborating with various teams to ensure data quality and robust reporting, mainly using dbt and SQL.

As a Director in the Data & Analytics team, you will lead client engagements, manage projects, develop strategies, create proposals, and mentor team members in data-driven initiatives.

Manage client data and analytics projects to design and implement data strategies, automation, visualizations, and predictive analytics. Translate data into actionable insights, lead cross-functional stakeholder engagement, scope and monitor budgets, and develop internal tools and templates. Apply finance/CPA knowledge where relevant and deliver client-facing presentations.

Manage client-facing data and analytics projects: define data strategy, build automation and ETL, develop visualizations and predictive analytics, drive transformation, manage scope/budget, and communicate findings to non-technical stakeholders while leveraging finance knowledge.

Develop and maintain value-based pro forma scenario and negotiation models, automate and standardize modeling, provide hands-on analytic support for IDN negotiations, collaborate with business partners on analytic solutions, and communicate results to stakeholders.

Embed within a core business area to define problems, build metrics/reports, run analyses and experiments, surface insights, and drive recommendations to deliver measurable business outcomes across growth, product, AI, and partnerships.

Embedded on a core business team, own analytics end-to-end: define problems, build reports and experiments, analyze data, surface insights, and drive recommendations that influence product, growth, AI/automation, or partnership decisions.

Embed with a core business unit to define problems, build metrics, run analyses, design experiments, surface insights, and drive data-informed decisions end-to-end across growth, product, AI, or partnerships.

Own analytics for an embedded business unit: define problems and metrics, build reports, run analyses, design experiments, and drive cross-functional recommendations to improve growth, product, AI, or partnerships.

Embed with a core business area to define problems, build metrics and reports, run analyses and experiments, surface insights, and drive recommendations to execution across growth, product, AI, or partnerships.

Embed with a core business unit to define problems, build metrics/reports, run analyses and experiments, and drive data-informed recommendations end-to-end to improve product, growth, AI, or partnerships.

Lead payments analytics by building scalable reporting, causal inference and ML models, designing experiments, partnering with product/engineering/finance to optimize payment processing, reconciliation, and settlement, and translating results into executive recommendations to drive global payments improvements.

Lead a team to develop data strategy and insights across multiple business functions, driving analytics evolution and ensuring data quality and governance.

The RevOps Analytics Engineer is responsible for maintaining data infrastructure, building reliable data systems, and supporting revenue analytics through effective data modeling and ETL/ELT processes.

The Senior Analytics Engineer will build and maintain data foundations for corporate reporting, translating business requirements into data models, ensuring consistent metric definitions and investigating data discrepancies for reliable reporting.

As a Senior Analytics Engineer, you'll design and manage data pipelines, develop reporting solutions, and provide actionable insights using data to improve healthcare delivery while collaborating across teams.

As a Revenue Analytics Manager, you will own reporting for Sales, Marketing, and Customer Success, build dashboards, automate workflows, and ensure data quality.

The Manager, Analytics Services will lead a team to deliver high-quality analytics projects, manage client relationships, and integrate AI solutions in healthcare analytics, focusing on business growth and client satisfaction.

The Lead, Advanced Analytics, Acquisition will analyze data, define metrics, conduct A/B tests, and collaborate with teams to drive growth and insights.

The Senior Analyst, Revenue Operations is responsible for delivering analytical insights, enhancing forecasting accuracy, and optimizing revenue processes while collaborating with various departments.

The Sales Analytics Manager will oversee sales analytics, implement AI-driven reporting solutions, and partner with various teams to enhance data governance and performance forecasting.