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.

Own and maintain the Propel PLM system to ensure accurate product data, BOMs, and integrations with ERP/CRM. Configure workflows, roles, and data structures; validate product and manufacturing documentation; support cross-functional teams; lead PLM projects; drive data quality improvements, user training, and continuous system enhancements to align PLM with production and supply chain operations.

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 Senior Data Analyst oversees performance reporting tools, automates data pipelines, conducts quantitative analyses, and communicates findings to various stakeholders.

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.

Entry-level data analyst supporting advertising insights and custom analytics engagements. Pulls and cleans competitive ad spend and creative data, runs share-of-spend and creative-surfacing workflows, builds early hypotheses, performs QA, and supports multiple accounts while learning internal tools and methodologies to grow into a client-facing analyst role.

The Data Analyst will perform data analysis, validation, and quality assessments, support MDM implementations, and collaborate with stakeholders to ensure accurate master data.

The Senior Product Data Analyst will lead analytics projects, providing strategic insights into SaaS product usage and customer behavior, while collaborating with various teams to drive business outcomes and improve product features.

Entry-level Data Analyst supporting Performance & Analytics for care operations. Build, validate, and QA recurring reports and dashboards (Retool/BI tools), pull and clean payer, clinical, and operational data, investigate discrepancies, maintain workflows and reporting-ready datasets, and support ad-hoc analytical priorities.

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 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.