Top Entry Level Data & Analytics Jobs in Denver & Boulder, CO

Collect, clean, validate, and analyze data from multiple sources. Write SQL queries, build Excel reports, and develop Power BI and Tableau dashboards. Identify trends, anomalies, and KPIs; prepare recurring and ad hoc analyses; maintain data quality; document processes; and communicate actionable insights to technical and nontechnical stakeholders.

Develop and optimize data pipelines using Python and SQL; integrate data through REST APIs; support ETL/ELT workflows; perform data cleaning, validation, and quality checks; troubleshoot processing issues; use Git for collaborative development; document workflows; and collaborate with engineers and analysts in a remote environment.

Analyzes and interprets data, evaluates results, and provides actionable insights to support strategic decision-making across departments.

Develop and maintain ServiceNow reports, dashboards, performance analytics, data extracts, and Power BI executive reporting. Build data models, KPIs, measures, and visualizations for operational performance, compliance, service health, and engineering effectiveness. Automate reporting, data collection, validation, distribution, and notifications using Power Automate, PowerShell, Python, or similar tools. Support Workspace ONE, Intune, macOS troubleshooting, monitoring, endpoint compliance, incident resolution, documentation, and change management.

Review complex geospatial questions, identify missing information, establish assumptions, and create detailed analytical workflows. Select appropriate data sources, tools, methods, validation steps, and deliverables for real-world applications such as crisis response, agriculture, site selection, and supply chain analysis. QA specialists review completed work and provide feedback against project guidelines. The role is fully remote, freelance, flexible, and project-based.

Analyze banking and financial crime data, develop and tune statistical and machine learning classification models, evaluate model performance, identify data quality issues, and recommend optimization strategies. The role uses Python and SQL for feature engineering, statistical modeling, automation, and large-scale data processing. Responsibilities also include documenting methodologies, reporting results to management and regulators, and collaborating with compliance, technology, business, and model governance teams.

Leads and manages an analytics engineering team while contributing to data transformation, modeling, quality, and delivery solutions. Establishes modeling and development standards, implements analytics engineering tools, supports client engagements, improves reporting and visualization processes, allocates team resources, mentors engineers, supports presales, and drives internal quality and process improvements.

Designs, develops, and optimizes high-availability relational databases supporting high-volume logistics services. Responsibilities include schema and database object architecture, SQL and T-SQL development, stored procedure implementation, performance tuning, scalability improvements, code reviews, prototyping, and end-to-end feature delivery. The role collaborates with engineering and infrastructure teams and may support database administration, cloud migrations, and modern data platforms.

Supports branch network performance reporting, dashboard development, data preparation, impact measurement, experimentation, and business insights. The analyst uses SQL and Alteryx or similar tools to prepare datasets, evaluate branch initiatives, maintain recurring reports, and communicate findings to stakeholders across retail banking, marketing, finance, and distribution. This is an early-career developmental role requiring careful analysis, clear communication, documentation, and collaboration.

Research and fact-check thousands of hospitals for Forbes’ Top Hospitals 2027 list. Responsibilities include verifying hospital names, profiles, addresses, CMS facility IDs, and ratings; conducting online research and phone calls; maintaining accurate records; entering data; and potentially reporting and writing short healthcare articles.

Manage and analyze mine-site operational data, consolidating planning, production, maintenance, and performance information into a centralized Technical Data Center. Deploy and support Python, Lua, SQL, and on-premises applications; monitor servers and infrastructure; troubleshoot operational applications; and collaborate with technical, operating, innovation, and business improvement teams on data integration and innovation initiatives.