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

Supports analytics teams by creating reports and dashboards, conducting data extraction, cleaning, validation, and basic analysis. Documents queries and business requirements, translates business needs into specifications, supports projects under guidance, and communicates findings to technical and nontechnical stakeholders. The role also develops foundational skills in data storytelling, governed cloud data platforms, metric validation, and workload organization.

Analyze large behavioral and transaction datasets, build reports and dashboards, collaborate with product and engineering to inform data-driven product decisions, automate analyses, communicate insights to stakeholders, and brainstorm new data uses to improve user experience.

Build and scale production Python pipelines for economic and financial climate-risk models. Responsibilities include transforming research prototypes into tested infrastructure, supporting statistical, econometric, and machine-learning modeling, cleaning large financial and hazard datasets, resolving data anomalies, and collaborating with engineering, product, and client teams to document outputs and communicate findings.

Build and optimize Alteryx workflows and data ingestion processes; extract, transform, normalize, and integrate enterprise data from multiple sources. Automate repetitive processing, ensure data quality, troubleshoot integrations, document workflows, and deliver datasets and analytical insights for internal business stakeholders. The role may also develop Tableau visualizations and use Python, PowerShell, or Bash scripting.

Analyze market, industry, competitor, and customer intelligence for Vistex’s served industries. Assess market opportunities, monitor competitors, identify trends, develop competitor profiles, and translate complex information into actionable insights. Findings support go-to-market strategies, product roadmaps, marketing direction, competitive positioning, pipeline development, and revenue growth. The role collaborates with industry, sales, marketing, product, and pre-sales stakeholders while managing multiple projects.

Loads, queries, extracts, validates, and refreshes client data; prepares reports and deliverables; identifies automation and process-improvement opportunities; supports UAT, system implementations, and quality assurance testing; and collaborates with cross-functional teams. The role translates client requirements into actionable tasks and requires SQL, relational database, Oracle, Unix, data analysis, reporting, and communication skills.

Reviews, develops, validates, and refines dashboards, reports, visualizations, calculations, data sources, KPIs, and analytical workflows across BI platforms. The role documents findings, provides structured feedback, troubleshoots reporting accuracy, and evaluates AI-powered agents and workplace connectors used in analytics processes.

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.

Performs accurate data entry, verification, updating, cleanup, organization, and maintenance across databases, spreadsheets, and digital systems. Maintains electronic records, converts documents into digital formats, prepares basic reports, retrieves information, tracks assignments, and supports scanning and filing. The role requires confidentiality, attention to detail, strong organization, dependable independent work, effective time management, and reliable remote-work capabilities.

Own data partner specification negotiations, data mapping, Ascend platform configuration, and internal QA across multiple implementations. Review file specifications, normalize schemas, validate test files, document data dictionaries, and route non-standard requests to Product or Customer Engineering. Coordinate with delivery and engagement teams on UAT, defects, readiness, and capacity constraints. Develop repeatable QA frameworks, implementation playbooks, procedures, and training materials while ensuring configurations meet quality standards before go-live.