Top Senior Analytics Jobs in Salt Lake City, UT

Lead product analytics: build and maintain dbt models and Looker dashboards, define KPIs, analyze funnel and user journeys, design and evaluate A/B tests, size roadmap impact, and deliver partner and ad-hoc insights to inform product and executive decisions.

Lead end-to-end analytical initiatives on partner enrollment funnels, ensure data quality, build reporting pipelines with BI/engineering, use AI-assisted tools to accelerate analysis, translate insights into strategic recommendations for leadership, and coach growing analytics team members.

Partner with sales leadership to define business requirements, design end-to-end analytics solutions (data models, semantic layers, dashboards), build scalable Power BI/Microsoft Fabric reporting, translate data into executive-ready insights, drive automation and standardization, mentor analysts, and influence business decisions with data-driven recommendations.

Design and implement scalable data platforms, build ETL/ELT pipelines, integrate multiple data sources, define KPIs, create dashboards and executive reports, ensure data quality/governance, and collaborate with stakeholders to optimize BI capabilities.

Build and maintain production data pipelines and foundations for People Analytics and AI-driven tools. Integrate HR systems (Workday, Greenhouse), design data models, ensure governance for sensitive employee data, support data science and reporting, and deliver dashboards and Streamlit apps. Optimize queries, enable LLM consumption with quality and latency controls, and collaborate cross-functionally to transition AI prototypes to production.

Lead product analytics for Guest or Host App: analyze large datasets, design and evaluate experiments, build metrics and reporting tools, apply statistical and causal methods, partner cross-functionally, present insights to stakeholders, and leverage AI to automate tasks.

Lead analytics partner to Community Support, driving data-driven roadmaps, scalable reporting and measurement, causal inference and experimentation, and improvements to agent/guest/host experiences via analytics, modeling, and stakeholder influence.

Lead the RevOps analytics function: manage an analytics team, own revenue reporting and forecasting, build measurement frameworks, enforce data governance, partner with BI/engineering, analyze funnel and retention metrics, and embed AI/automation to improve revenue predictability and GTM performance.

Lead analytics for law firm operations by writing advanced SQL and Python/R scripts, building executive dashboards, standardizing KPIs, analyzing case lifecycle metrics, identifying bottlenecks, and delivering actionable recommendations to drive capacity planning and process improvements.

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

Lead the Payments Insights Analytics team, utilizing data and AI/ML for strategy execution, operational excellence, and stakeholder communication.

The Senior Data Scientist will design and deploy time-series forecasting models, collaborate with stakeholders, and operationalize models in cloud environments, focusing on demand planning across various industries.

Design and maintain a formal analytics data layer (AWS Glue, Athena/Presto, LookML); build data models, pipelines, and automated quality checks; investigate anomalies; document metrics and lineage; mentor analytics team members and promote best practices.

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.

Lead analytics and data-product initiatives for healthcare clients: gather reporting requirements, design and develop reports/products, test and validate, provide post-implementation support, and partner with stakeholders to drive adoption and measurable value.

Lead-level analyst who designs, develops, and delivers reports, dashboards, and data solutions (SQL, Power BI, SSRS, Excel). Analyzes complex healthcare, financial, and operational data, ensures data quality and ETL processes, mentors analysts, manages analytics projects, drives automation and process improvements, and presents insights to leadership and stakeholders.

Lead identification and quantification of issuance leakage across acquisition, application, approval, and funding funnels. Analyze digital customer journeys and conversion gaps, run root-cause diagnostics, design experiments, build executive dashboards, and translate findings into prioritized, quantified business recommendations partnering with Product, Marketing, Credit Risk, Operations, and Engineering.

Lead design and governance of enterprise ontologies, knowledge graph architecture, ingestion pipelines, and semantic layers. Enable semantic interoperability across data products, implement inference and reasoning, and establish standards, versioning, and data contracts to support scalable graph-driven analytics and AI augmentation.

Lead design and implementation of data models, write optimized SQL at scale, enable semantic layers and AI tooling, manage analytics infrastructure, build frontend data surfaces, and partner with product and engineering to structure source systems for reporting.

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

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

Own marketing channel performance tracking, reporting, and analysis. Design and analyze experiments (A/B, incrementality), build dashboards in Looker/Tableau, support LTV and forecasting models, identify measurement gaps, and translate analysis into clear recommendations for Growth, Marketing, and Finance stakeholders.

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.

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