Top Data Analyst Jobs in Denver & Boulder, CO

Partner with HR and business leaders to deliver workforce analytics, build automated dashboards and models using SQL, Python, and Tableau/Alteryx, ensure data quality, and provide actionable insights and forecasts to inform people strategy.

As a Data Analyst II, you will enhance marketing strategies by auditing current data processes, creating dashboard reports, and conducting A/B tests with statistical validation to drive customer engagement and growth.

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 data analysis and reporting for the Trading team, build and maintain dashboards and governed analytics, deliver quantitative research, mentor juniors, and present insights to stakeholders to support decision-making and next-gen trading platform development.

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.

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.

Process and validate telecommunications orders (LSRs, ASRs, DSRs, broadband), resolve customer tickets, maintain order/status records, liaise with carriers and internal teams, perform QA on billing/orders, support onboarding/training, and drive process improvements and automation initiatives to improve service delivery.

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.

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.

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.

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.

Analyze business questions using SQL and Excel, build dashboards and reports, synthesize findings into clear presentations, and deliver actionable insights to senior stakeholders to drive strategy.

Write and optimize complex SQL to analyze automotive marketing and inventory data; audit and standardize large datasets; investigate CRM/data discrepancies; build and maintain client-facing BI dashboards and reports; perform QA on datasets and reports; collaborate with US reporting team and fulfill ad-hoc data requests.

Perform ad hoc and ongoing data analysis to drive product decisions for CMS: implement and audit web analytics tagging, integrate Qualtrics and other qualitative sources, build dashboards and ETL pipelines, monitor system performance via Datadog, analyze user behavior (including LLM product metrics), and synthesize mixed-methods insights to inform the team.

Partner with clinical and operations leaders to build scalable real-time reporting, measure team performance and SLAs, perform root-cause analyses, advance data modeling and best practices, and enable stakeholder self-service using BI and AI capabilities.

Own and deliver analytics solutions to support operational and financial decisions. Define reporting requirements and KPIs with stakeholders, validate and reconcile data, write and optimize SQL, support ETL pipelines, and develop/maintain Power BI dashboards to produce actionable insights for Revenue Cycle Management.

Support federal clients with organizational assessment, data analytics, and visualization. Develop and implement analytic tools/reports, prepare briefings, maintain SharePoint/Teams, collaborate with stakeholders, manage project tasks, and support implementation of recommendations. Remote role with occasional travel; Power Platform experience preferred.

The Marketing Data Analyst will analyze performance data across marketing and sales channels, develop dashboards, and provide insights to improve customer engagement and ROI.

The Senior Marketing Data Analyst will enhance marketing performance through data analysis, optimization strategies, and collaboration with marketing stakeholders, focusing on Checking and Deposit Acquisition.

The Data Analyst will maintain KPI standards for Customer Support, build dashboards, produce analyses, and lead metric alignment conversations, ensuring accurate data interpretation and decision-making support.

Design and run evaluation frameworks to assess third-party vendor data for fraud detection. Build lift analyses, backtests, and champion/challenger tests; profile vendor datasets for quality and coverage; collaborate with fraud, product, and data engineering to define ingestion and testing requirements; translate findings into actionable recommendations and maintain an internal knowledge base; support ad hoc analyses on fraud trends and model performance.

The Data Analyst will perform data analysis and interpretation for reporting, work with unstructured data, and engage with business users to identify requirements.