Top Remote Analytics Jobs in Provo, UT

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

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.

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.

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

Lead global partner analytics and planning for partner GTM motions. Build dashboards, business models, AI-enabled workflows, and executive reports to support partner planning, incentives, coverage, performance management, and cross-functional decision-making across hyperscalers, ISVs, marketplaces, and reseller channels.

Own metrics and datasets that measure cloud, storage, streaming, and ML infrastructure efficiency. Build end-to-end analytics: metric frameworks, pipelines, dashboards, and narratives that inform executive and engineering investment decisions. Pioneer methods to quantify AI and agent-driven productivity, identify efficiency opportunities, and partner with data engineers and data scientists to deliver trusted, reusable insights and recommendations.

Hands-on Adobe Customer Journey Analytics (CJA) Lead responsible for designing, configuring, and executing CJA solutions, enabling AEP data flows, defining measurement frameworks, mapping data sources, and delivering reporting while partnering with stakeholders and providing technical architecture and execution.

Manage design, development, and delivery of data products and analytics solutions. Lead and coach an analytics team, gather requirements, improve processes, reduce technical debt, collaborate with platform and product architecture, and ensure solutions meet internal and external client needs.

Lead infrastructure analytics for compute, storage, and networking: design scalable data pipelines, define core metrics, build dashboards and APIs, ensure data quality and governance, drive instrumentation fixes, and advise executives on capacity, utilization, and readiness.

Lead sales analytics and planning for Consumer and Fleet channels. Build MQL-to-SQL frameworks, CRM infrastructure, lead scoring, forecasting models, and executive dashboards. Partner cross-functionally with Marketing Analytics, IT, and Sales to ensure data governance, reporting cadence, and scalable sales intelligence.

Lead and build the Risk Analytics function: define pricing methodology and risk frameworks, own portfolio and pricing strategy, convert monitoring into decision systems, architect the Risk Analytics data layer (dbt/Snowflake), mentor senior data scientists, and represent risk recommendations to senior leadership to drive business decisions.

Lead analytics strategy and enterprise semantic/reporting layers across QuickSight/Tableau and Redshift/Athena. Partner with data engineering on domain models, enforce data quality/governance, optimize analytics performance/cost, mentor analysts, and communicate insights to executives.

The role involves building analytics tools and frameworks to support Airbnb's international growth strategy, requiring deep data expertise and collaboration with various teams.

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.

Lead analytics for Community Marketing programs: define measurement frameworks, build Power BI dashboards, run analyses across referrals/events/COI, deliver executive insights, forecast leads/opportunities, and partner cross-functionally to optimize program performance and reporting.

Senior AWS Analytics Engineer. Posting contains no detailed responsibilities or qualifications beyond the job title.

Own the Finance & Operations data layer: ingest and model data from systems (NetSuite, Ramp, Pigment) into Snowflake/Omni, ensure data quality and metric governance, build dashboards and reports, collaborate with Finance/Ops stakeholders, and automate reconciliation and reporting workflows.

Lead current-year and long-term AP volume forecasting using statistical and AI/ML methods; diagnose supply-demand drivers; close analytic data gaps; translate analyses into strategic recommendations; mentor staff and communicate forecasts and risks to senior stakeholders across College Board.

Partner with Product, Marketing, Growth, Engineering, and Business teams to analyze user behavior, build dashboards and self-serve reports, support A/B testing and experiment measurement, create user segments and cohorts, monitor KPIs, and communicate actionable insights to stakeholders to improve engagement, conversion, retention, and campaign performance.

Lead enterprise adoption and toolchain integration for business analysis across federated teams. Design enablement curriculum, integrate standards and AI-enabled tooling (Azure DevOps, ServiceNow, Nexus, Power BI), build decision-oriented dashboards and leading indicators, drive adoption and governance, surface portfolio trends, and partner with stakeholders to improve delivery predictability and compliance.

Design and deliver reporting, dashboards, and analytics for higher education advancement and constituent data. Gather requirements, define KPIs, perform SQL-based analysis and data validation, and build actionable Tableau visualizations. Advise clients, run workshops, collaborate with data engineering/CRM teams, document business rules and tests, and support adoption and analytics modernization initiatives within a consulting environment.

Own and architect the semantic layer and metrics/metadata for the data platform (Databricks/GCP). Build AI-ready models, enforce modeling and documentation standards, implement observability/testing for pipelines, enable self-serve analytics, and collaborate across product, clinical, and business teams to translate questions into reliable data solutions.

Owner of data platform modernization: design and migrate legacy systems to Kimball-style dimensional models and star schemas; build reliable production data pipelines; enforce data hygiene and validation; champion dbt best practices; mentor junior engineers; collaborate with analysts and stakeholders to ensure scalable, well-documented data models and platform observability.

Provide geospatial and market intelligence to support leasing, marketing, investments, and development. Maintain geospatial datasets and trade areas, perform location-based analyses integrating internal and third-party data, build maps/dashboards/reports, and apply AI-enabled tools and automation to improve research, reporting, and decision support across the organization.

Lead credit underwriting, pricing, verification, and portfolio performance for personal loans. Use data and ML/AI to design automated decisioning, manage credit/fraud risk, forecast losses, and present strategies to leadership and investors. Collaborate cross-functionally and build vendor/alternative-data strategies to drive profitable growth while keeping losses within risk appetite.