Top Data Analyst Jobs in Denver & Boulder, CO

Lead data strategy and analytics for Compliance and AML, develop ETL and validations, quantify regulatory risk, communicate insights to stakeholders and regulators, and drive cross-functional compliance initiatives.

Support Finance and Sales by reconciling and validating revenue KPIs (ACV, ARR, renewals), building reporting datasets and dashboards, collaborating with CRM and data engineering teams, and participating in month-end and quarter-end close activities. Provide ad-hoc analysis and stakeholder-facing explanations of metric derivation and data quality.

The Lead Data Analyst (Network) drives data-driven initiatives, dissects datasets, and provides actionable insights to enhance business performance and network efficiency.

Lead data analyst responsible for advanced analytics, real-time performance dashboards, network capacity modeling, and generating actionable insights for third-party service providers. Drives testing and pilots, analyzes stakeholder feedback, and serves as an internal analytics subject-matter expert to inform network strategy and operational improvements.

Analyze transactional metrics to identify inefficiencies, financial risks, and fraud; produce and validate daily/weekly/monthly reports and proactive alerts; consolidate and validate data sources for reporting; recommend process improvements to improve collections efficiency and customer satisfaction; deliver presentations and special-project analyses to senior management while leveraging automation and AI tools.

Validate and review CO APCD-derived data products using SQL and visualization tools, perform output comparisons and project-level analyses, follow quality control standards, document findings, and communicate results to technical and non-technical stakeholders while supporting continuous improvement of data QA processes.

Analyze sales, marketing, and customer success performance, including pipeline, funnel conversion, campaigns, retention, and revenue drivers. Build and maintain dbt models and marts using Salesforce and modern data-stack tools, while owning data quality and documentation. Contribute to Lighthouse, a BI-as-code platform, and develop AI-assisted analytics workflows. Partner with stakeholders to frame ambiguous questions, deliver recommendations, and communicate progress in two-week sprints.

Design, implement, and validate data mapping, transformation, and integration solutions for payment integrity. Investigate and resolve complex data quality issues, create mapping specs and documentation, partner with stakeholders, and mentor analysts to improve data quality and automation.

Support analytics by cleaning, validating, and transforming data; build dashboards and KPI reports; perform trend, cohort, and A/B testing analyses; improve data pipelines and forecasting; present insights to cross-functional teams.

Build and maintain Rayda’s data warehouse, analytics infrastructure, data models, transformation layers, pipelines, and workflows. Integrate product, billing, and customer interaction data from multiple platforms, improve data quality and governance, and create reliable datasets and analytical models. Enable self-service analytics and collaborate with Product, Growth, Commercial, and leadership teams to uncover usage patterns, churn risks, and expansion opportunities.

Supports data collection, cleaning, validation, reporting, dashboard preparation, and basic analysis. Tracks business and product metrics, identifies trends, documents datasets and processes, responds to ad hoc requests, and helps improve data usability while collaborating with cross-functional teams.

Lead analytics and data science for long-term care insurance claims: analyze healthcare and claims data, build predictive models, perform EDA, prototype solutions, collaborate with stakeholders, and translate insights into business recommendations to improve reporting and decision-making.

Analyze large healthcare datasets to extract insights, build data models, reports and dashboards, ensure data quality, collaborate with cross-functional teams, and present findings to stakeholders.

Build SQL-based data models, reports, and Tableau dashboards for financial and SaaS metrics including ARR, RPO, and customer retention. Analyze and clean data, improve reporting accuracy and data quality, document metric definitions, and deliver actionable insights to Finance and Revenue Operations stakeholders. Use AI-assisted tools to improve analytics efficiency, manage work in Jira, troubleshoot data issues, and collaborate cross-functionally. Minimal travel of approximately 10% or less is required.

Supports data cleansing, quality checks, reporting, dashboards, data-source and metadata maintenance, data integrity, and normalization. Translates reporting requirements and analytical results for nontechnical audiences, handles sensitive information securely, and assists end users with reports and dashboards. Works under senior analyst guidance in a federal environment and must be able to obtain and maintain a Public Trust clearance.

Develops scalable data models, dashboards, reports, and analytical solutions that support business decisions. Partners with stakeholders to translate requirements, ensures data accuracy and usability, provides technical guidance to end users, documents architectures and processes, and communicates findings to technical and non-technical audiences. The role requires advanced Spotfire, SQL, and business intelligence experience, plus familiarity with modern data platforms and AI-assisted development tools.

Provide insights and recommendations to improve end-to-end purchase customer journeys across web and app for B2C and B2B. Lead A/B testing and experimentation, ensure accurate data collection and impact measurement, build self-service reporting and visualizations, query and process data, and present findings to stakeholders and senior leadership.

The Lead GTM Data Operations Analyst will operate and extend AI-driven data quality pipelines, optimize agent outputs, and monitor offshore resolution teams, ultimately improving data accuracy and management in a dynamic, evolving environment.

Perform independent healthcare analytics projects for clients using statistical tools, predictive modeling, BI reporting, and data visualization. Build reports and analyses with R/SAS/SPSS and BI tools (Cognos, Business Objects). Maintain client relationships and report to a Senior Consultant.

Lead client-facing analytics engagements: translate ambiguous business questions into data models, dashboards, and KPIs; write production-quality SQL and dbt models; build BI reporting; apply AI tools to accelerate analysis; drive proactive insights; set stakeholder cadence; and mentor junior analysts to ensure adoption and delivery.

Analyze and integrate federal grants management data from multiple sources; maintain databases and systems; develop reports, dashboards, presentations, and visual data stories; conduct testing, validation, quality control, and process improvement; support grant administration, training, documentation, and stakeholder coordination for the Office of Head Start.

Support implementation of Bluesight SaaS products by helping hospital customers extract, transform, load, validate, reconcile, and analyze data. Configure infrastructure, troubleshoot technical issues, write and update scripts and SQL, document processes, and collaborate with implementation, product, and engineering teams to improve data pipelines. The role combines customer-facing communication with technical data integration work involving cloud services, databases, command-line tools, and multiple programming languages.

Design, build, and maintain Power BI and Tableau dashboards; analyze large, complex datasets using SQL, Python, and statistical methods; partner with data engineering and business stakeholders to ensure data quality; translate findings into clear, actionable stories and executive-level presentations; support firmwide analytics growth and automation.

Lead enterprise insurance analytics initiatives supporting underwriting, claims, finance, and operations. Build reporting and dashboards, ensure data integrity across TPAs and systems, support captive program performance, partner with actuary and IT, and present actionable insights to leadership.

Lead analytics to improve player experience, engagement, retention, and monetization. Analyze player lifecycle, run cohort and funnel analyses, design and evaluate A/B tests, build dashboards, define product metrics, investigate KPI changes, and partner with product, marketing, engineering, and data teams to deliver data-driven recommendations and improve data quality.