Top Data Analyst Jobs in Denver & Boulder, CO

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.

Manage HMDA and CRA data integrity, perform validation and quality control, coordinate annual LAR and CRA submissions, resolve data discrepancies with cross-functional teams, maintain documentation and controls, support regulatory exams and audits, monitor regulatory changes, and prepare management reporting on data quality and submission readiness.

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.

As a Principal Analyst in Growth Marketing, you will lead analytics for acquisition channels, applying advanced analytical techniques to drive business growth and improve marketing performance while collaborating across teams.

Build and maintain dbt models, write SQL to investigate and validate data, implement data quality checks, document lineage and metrics, resolve production issues (including on-call), and partner with analysts and business teams to deliver production-ready data products using modern warehouse tooling and AI-assisted frameworks.

The Data Analyst II analyzes data using SQL, Python, and R to provide actionable insights, improve processes, and support decision-making across teams. Responsibilities include developing forecasts, liaising with stakeholders, and presenting findings to executives.

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.

As a Staff Data Analyst, you'll drive data analysis, build business intelligence tools, and collaborate across teams to optimize Upstart's servicing strategy, while mentoring junior analysts.

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

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.

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.

Manage and audit employee data across HR systems, process personnel actions, respond to Tier 2 employee inquiries, track case resolutions, and collaborate with stakeholders on system requirements and process improvements.

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 Operations and Logistics Data Analyst builds and maintains reporting infrastructure, analyzes fulfillment data, ensures data integrity, and supports CX reporting to optimize performance across operations.

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.

The Data Analyst will translate business needs into data requirements, analyze data across systems, and support data management activities for the DSCA Chief Data Officer.

The Data Analyst will build key data models and metrics for decision-making, partner with stakeholders for analytical insights, create datasets for self-service reporting, and ensure data reliability through quality checks.

As a Forward Deployed Data Analyst, you will configure and implement data systems for clients, ensuring their analytics are accurate and actionable. You'll work with teams to refine metrics and improve data processes, ensuring value from day one.

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

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.

Perform data extraction from SQL/NoSQL systems, validate and transform data, and run statistical and psychometric analyses (IRT, reliability, norming). Validate assessment logic, define quality metrics, design research and simulation studies, and present findings via reports and dashboards. Collaborate cross-functionally and maintain current psychometric and data engineering practices.

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

Partner with GTM, Clinical Strategy, and Finance to build and maintain dbt models, client-facing reports, and dashboards. Perform SQL-based analyses, ROI and clinical outcomes reporting, and translate insights for non-technical stakeholders. Ensure data reliability through testing, code review, and collaboration with Data Engineering; support ad-hoc requests and automation of reporting.