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.

Analyze large operational datasets to optimize field efficiency, logistics, and supply chain pipelines. Build forecasting and headcount models, create dashboards and KPIs in Tableau, apply predictive analytics/ML to automate reporting, lead cross-functional alignment, and present data-driven recommendations to field and executive leadership to reduce costs and align capacity.

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.

Design scalable data structures for marketing attribution and audience segmentation, build SQL/Python workflows, create automated Tableau dashboards, run A/B tests with statistical rigor, and integrate AI-driven automation to accelerate reporting and insights for marketing stakeholders.

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

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.

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.

Develop and improve TransUnion's IP geolocation technology by analyzing large datasets, implementing automation algorithm improvements, and providing analytic insights. Collaborate with engineers and data scientists, use SQL/R/Python/MongoDB/BigQuery, and communicate findings to nontechnical stakeholders. Hybrid role with regular in-office work.

Lead ownership of client billing data and infrastructure for Finance: run reconciliations, investigate billing issues, build BI dashboards, automate workflows with SQL/Snowflake, monitor revenue leakage, and support Billing 2.0 UAT while training Finance on reporting and Looker standards.

Partner with People teams to turn HR and org data into actionable insights. Build complex queries, statistical analyses, dashboards, and a centralized people data repository. Drive data governance, data quality, and stakeholder communication to support hiring, retention, productivity, and workforce decision-making.

Lead end-to-end analytics to optimize customer lifecycle, retention, LTV, and engagement. Build reporting suites and interactive dashboards, perform advanced statistical analysis, collaborate with Data Science on data prep and features, leverage generative AI and automation, mentor junior analysts, and translate insights into business recommendations.

Perform structured data conversion, cleansing, validation, and mapping for system implementations. Execute validation scripts, support UAT, document discrepancies, reconcile legacy and converted data, and escalate anomalies to senior consultants while maintaining organized records and templates.

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.

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.

Support marketing analytics by analyzing digital channel performance, building and maintaining KPI dashboards, ensuring data accuracy, and collaborating with cross-functional teams to turn insights into actionable recommendations.

Collaborate with business teams to define analytics requirements, explore and model operational and financial data, produce forecasts and recommendations, and build dashboards and visualizations to support decision-making. Contribute to data stewardship, metadata, data quality remediation, and liaison with enterprise analytics for data model needs.

Support Items Master Data Management by collecting, cleansing, and analyzing supply chain product, contract, and pricing data. Build SQL-based reports and dashboards, ensure data quality and governance, support system implementations and migrations, and collaborate cross-functionally to drive standardization and operational improvements.

Own support analytics for User Operations: build dashboards and recurring reports, track north-star metrics (cSAT, TTR, QA, escalations), instrument Zendesk, connect support to product/customer data, quantify operational costs of bugs, and measure AI-driven support performance.

Own and maintain data products end-to-end for sector teams, analyze large datasets, refine methodologies, automate workflows using AI and tooling, collaborate with Research, Engineering, and Product, and deliver accurate, client-facing insights and improvements.

Build scalable GTM and product analytics to inform revenue, retention, and growth decisions. Partner with Sales, Customer Success, Finance, Product, and Data Engineering to deliver dashboards, models, and executive data stories; validate data quality; measure ROI; and enable self-service reporting across the lead-to-quote-to-cash journey.

Senior Data Analyst cleans and prepares data, builds reports and dashboards using Power Platform, Excel, DAX, M, R or Python, develops data models and predictive/ML solutions, supports client/internal projects, and may lead others or assist business development.

Partner with cross-functional teams to design experiments, analyze large datasets, build dashboards and metrics, identify trends and customer behaviors, improve data quality and instrumentation, and provide actionable recommendations that drive strategic decisions and operational improvements.

Work across data infrastructure and analytics: build and maintain dbt models, ingest and transform data, create dashboards and semantic layers in Power BI, validate AI-generated code, partner with stakeholders to deliver analyses and data products, and improve data governance and documentation.

Design and analyze experiments, measure campaign incrementality, identify customer segments and engagement opportunities, validate tracking and anomalies, surface actionable insights, and build scalable measurement infrastructure with cross-functional partners.