Top Data Analyst Jobs in Denver & Boulder, CO

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.

The Data Analyst in Revenue Operations will analyze sales data, build models, and create reports using SQL, Excel, and BI tools to empower business decisions.

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

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 Senior Customer Lifecycle Analyst leads data-driven projects focusing on customer retention, engagement, and lifetime value, leveraging advanced analytics and visualization tools to provide business insights and recommendations.

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.

Lead strategic analytics and partner with senior leadership to drive growth, margin, and retention initiatives. Build interactive reporting (Python/Streamlit, BigQuery-connected Google Sheets), perform deep EDA in Jupyter, model and clean data with SQL and dbt, integrate secure AI-assisted tools and automation, ensure analytical quality, and translate insights into measurable business outcomes.

Support cost management and project controls for data center construction by aggregating, cleaning, and analyzing cost and schedule data; build EAC templates, dashboards, and executive reporting; perform benchmarking and reconcile multi-source datasets; establish baselines and unit rate libraries; communicate insights to technical and non-technical stakeholders and assist with ad hoc analyses.

Support healthcare research projects by cleaning, managing, modeling, and visualizing large claims and survey datasets (e.g., CMS, MEPS). Produce statistical analyses, documentation, and client-ready reports using SAS and Python/R while following quality assurance and project timelines.

As a Data Analyst Intern, you will assist in data collection, cleaning, analysis, and visualization to support business decisions in a remote setup.

Analyze large training and telemetry datasets using SQL and Python to measure ROI and human risk, build executive dashboards in Looker/Tableau, audit data integrity, run behavioral analyses to identify high-risk cohorts, and present actionable insights to federal stakeholders while partnering with Data Engineering and Product.

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.

Support data collection, cleaning, and preliminary analysis. Write and run SQL queries, use statistical tools and Python, produce visualizations, document methods, troubleshoot analytics tools, and collaborate with cross-functional teams to deliver actionable insights.

Partner with product squads to own end-to-end analyses: define questions, write SQL, model event-level data, build dashboards and self-serve tools, evaluate experiments, and deliver clear, actionable recommendations to PMs, marketers, and leaders.

Analyze commercial campaign performance, build dashboards and reports, provide actionable insights for Client Services and Sales, manage target lists and data quality, and improve reporting through automation and AI-enabled tools to support commercial growth.

Perform product and player-behavior analysis for Marvel Strike Force using SQL/Python and reporting tools. Build recurring KPI reports, design/validate analytics tracking and experiments, partner with cross-functional teams, and use AI-enabled tools to accelerate workflows while ensuring data quality, privacy, and clear executive-ready insights.

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 analytical projects, develop quantitative models, analyze datasets for insights, and translate findings into business recommendations, primarily supporting client decision-making.

Assess and validate payer-submitted and processed claims data for completeness, accuracy, and documentation. Run SQL queries, support QA, identify best practices, develop data management/analytics capabilities, and communicate findings to stakeholders while collaborating with the Data Quality team.

Support randomized control trials and A/B tests for Party at the Polls: maintain experimental data tables, prepare samples, analyze results (pre/post-election), prioritize sites, and produce reports and timely program performance analysis.

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.

Design, build, and maintain Looker/LookML reporting and dashboards; partner with stakeholders to gather requirements; write performant SQL and dbt models; ensure data quality and documentation; analyze large datasets and deliver insights; grow into data engineering tasks (pipelines, orchestration, integrations).

Collects and organizes information for user manuals, training, installation guides, proposals, and reports. Edits functional descriptions and system specifications. Prepares and maintains systems, programming, and operations documentation and procedures. Maintains internal documentation library, supports financial/administrative tasks, coordinates documentation services, and works with Agile teams in a secure remote environment supporting government projects.