Top Senior Analysis Reporting Jobs in Salt Lake City, UT

This role involves writing user stories, supporting agile team processes, and driving customer discovery to enhance technology solutions for clients.

The Actuarial Specialist produces analyses, manages projects, and oversees team workload to enhance actuarial processes in the organization, ensuring business growth and profitability.

The Data & Analytics Architect will design and implement analytics solutions, support client engagements, and lead data architecture projects, requiring extensive technical and consulting skills.

The Senior Fraud Strategy Analyst will design and optimize fraud strategies, monitor performance, develop metrics, and collaborate with teams to enhance fraud detection.

Design, build, and maintain an internal data platform enabling secure, governed access for engineering and analytics. Partner with architects, implement data pipelines and automations, enforce security and compliance, support platform services, recommend architecture improvements, mentor teams, and drive adoption of scalable, self-service data capabilities.

The Senior Analyst will support product engineering efforts by analyzing digital solutions, enhancing user experiences, and collaborating across teams to deliver insights and improvements.

The Senior Manager, Commercial Forecasting and Insights leads global forecasting, analytics, and insights to drive revenue performance through strategic partnerships with sales and finance leadership.

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.

Lead analytics strategy and delivery for healthcare clients: gather reporting requirements, design and build enterprise data platforms (Databricks/lakehouse), develop and validate reports (including Epic reporting), influence decentralized data teams, and provide post-implementation support and modernization.

Evaluate and optimize AI-driven medical coding by analyzing automation performance, identifying automation opportunities and risks, escalating issues to engineering and compliance, and collaborating with data science, coding, and clinical teams to produce reports and communicate impact to stakeholders and customers.