Top Senior Data & Analytics Jobs in Ogden, UT

As a Client Insights Lead, you will develop analytics strategies, connect cross-channel data, deliver actionable insights, and enhance client marketing decisions.

Design, develop, and maintain Microsoft Power Platform applications and dashboards (Power Apps, Power Automate, SharePoint, Dataverse, Power BI). Translate stakeholder requirements into technical solutions, create data visualizations and recurring reports, perform trend analysis, troubleshoot integrated solutions, and support system design, configuration, and continuous improvement to improve operational performance and remediation tracking.

Lead the design and implementation of algorithmic trading strategies, oversee technical infrastructures, and mentor a multidisciplinary team while managing performance analysis and risk.

Lead enterprise data architecture, migrations, and data services; define standards and roadmaps; oversee complex ETL and third-party integrations; deliver analytics, BI dashboards, and commercialization of AI analytics offerings; build the Data Strategy & Services organization and ensure continuity for legacy clients while partnering across Product, Engineering, Sales, and Customer Success.

Lead market and client-level fundraising data analysis and publish original research and benchmarks. Partner with Sales, Customer Success, and Marketing to produce ROI cases, client insights, and thought leadership. Present findings publicly at conferences, build repeatable insight frameworks and tools, and translate data into persuasive narratives for advancement leaders.

Lead a team delivering actuarial, regulatory, and operational statistical reports and analytics. Ensure compliance with bureau submissions, drive reporting automation, define data requirements, lead UAT for policy/claims systems, and manage vendor and regulator interactions to support pricing, reserving, underwriting, claims, and financial analytics.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

Lead post-sales and revenue analytics by integrating product telemetry, support signals, and revenue data. Build scalable data models, reusable datasets, and semantic layers. Define SaaS metrics, forecast revenue and usage, predict expansion and churn, and deliver dashboards and insights to drive renewals, expansion, and revenue growth.

The Senior Analytics Engineering Manager will oversee analytics engineering vision, manage a team, ensure data quality, and drive data-driven decisions across departments.

Lead people-analytics strategy for Talent Acquisition and Talent Development. Drive end-to-end analysis of complex workforce problems, deliver evidence-based recommendations to senior leaders, ensure data governance and quality, coach junior analysts, build metrics frameworks, and conduct benchmarking and external research to inform workforce strategy.