Top Data Analyst Jobs in Denver & Boulder, CO

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

Analyze transactional and operational payments data to monitor performance, detect risk and fraud, and improve collections. Build, validate, and automate daily/weekly/monthly reports and alerts, consolidate data sources, deliver insights to stakeholders, and support special analytics projects to drive operational efficiency.

Perform advanced analysis of large datasets to optimize field efficiency and logistics, build forecasting and headcount models, create Tableau dashboards, lead cross-functional alignment, use predictive analytics/AI to automate reporting, and present data-driven recommendations to operations leadership.

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.

Lead Data Analyst responsible for advanced analytics, real-time dashboards, capacity modeling, and network performance insights. Collaborates with stakeholders to identify inefficiencies, run tests and pilots, and deliver actionable recommendations to improve service provider performance and network operations.

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.

Lead contact center analytics by analyzing large datasets, building predictive models, ensuring data quality, and creating dashboards. Collaborate with cross-functional teams, identify AI/automation opportunities, present insights to executives, and maintain data privacy and repeatable reporting processes to improve customer experience and operational efficiency.

As a Lead Data Science Analyst, you will develop predictive models, perform statistical analyses, and implement AI-driven solutions to enhance the sales customer lifecycle and drive business insights.

Design and implement end-to-end SQL data pipelines and R/Python/SAS statistical analyses for HEOR/RWE observational studies using Komodo's Healthcare Map. Validate and document analyses, apply epidemiologic methods and advanced statistical techniques, produce publication-ready deliverables, and present results to stakeholders while maintaining version control and reproducible research practices.

Lead growth analytics for acquisition and activation funnels: measure channel performance, build data models and KPI reporting, run experiment analysis, and translate insights into business recommendations. Partner with Growth product team and leadership to visualize results and drive strategy.

Lead development of compliance dashboards, automated reports, and integrations between trade compliance systems and ERPs. Translate regulatory data into visuals, manage integration and implementation projects, coordinate cross-functional teams, and serve as subject-matter expert to drive compliance improvements and automation.

Support business decisions by gathering, organizing, and interpreting data; build data pipelines, dashboards, and AI-enabled solutions; modernize workflows using statistical analysis, cloud platforms, and automation to improve operational efficiency.

Provide advanced technical support and subject-matter expertise for Relativity platforms (RelativityOne/Server), design and maintain complex workspaces and permissions, configure analytics/processing/imaging, develop event handlers and advanced search logic, deliver client-facing training/demos, mentor junior analysts, review deliverables, and maintain eDiscovery SOPs and best practices.

Lead analytics and reporting for value-based contracts: build and maintain performance evaluations, calculate incentive distributions, translate business requirements into technical specs, partner with Data Engineering to ensure data quality, write SQL and Python analyses, gather stakeholder feedback, and deliver ad-hoc and executive-level insights to guide strategic decisions.

Analyze digital customer journeys and site behavior to identify friction, explain marketing performance, and provide actionable insights. Maintain dashboards, support A/B and multivariate testing, collaborate with developers on tagging and tracking, and drive optimization to improve conversion and retention.

Perform data collection, cleaning, validation, exploratory analysis, and visualization to produce dashboards and reports. Write SQL and use Python/R and visualization tools to generate insights, support cross-functional teams, maintain documentation and data quality, and assist senior analysts on modeling and forecasting.

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.

Audit and reconcile marketing and lead data end-to-end, maintain campaign tracking and platform integrations, troubleshoot data flow issues, manipulate large datasets to identify discrepancies, coordinate with vendors and stakeholders, and recommend process improvements to ensure accurate marketing-to-intake reporting.

The Business Intelligence Data Analyst II supports reporting, dashboards, and data-driven insights, working closely with Business Intelligence and Data Engineering teams. Responsibilities include optimizing data structures, leading data modeling, collaborating on requirements, and monitoring data feeds.

Own end-to-end analytics for the Pro product: build production data pipelines and dbt models, define north-star metrics, design dashboards and full-funnel reporting, lead A/B experimentation and causal inference, embed AI tooling, and deliver clear data-driven recommendations to product and leadership.

Own BI analytics using a modern data stack to generate insights, build dashboards and self-serve tools, partner with stakeholders, and deploy AI-driven reporting and natural-language query solutions.

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.

Support quality control and assurance for CO APCD data products by running validation checks, comparing outputs, and preparing reviews. Use basic SQL and data visualization tools to validate datasets, communicate findings to technical and non-technical audiences, and follow issue-resolution guidance under the Quality Control Manager. Contribute to process improvements and assist larger analytic projects to ensure accurate, complete, and usable data.

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.