Top Remote Entry Level Data & Analytics Jobs in CO

Reviews and analyzes large business datasets for accuracy, completeness, relevance, privacy, and quality. Conducts document reviews involving PII, identifies data issues and anomalies, provides feedback to support AI training, refines quality assurance standards, and communicates findings to project stakeholders while maintaining data privacy and security compliance.

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.

Reviews and annotates Japanese-language text and images for AI training. Tasks include drawing bounding boxes, answering structured questions, writing short summaries, and following annotation guidelines. The role is fully remote, text- and image-based, requires 30–40 hours weekly for at least six months, and provides on-the-job training with no prior experience required.

Monitors healthcare data workflows, validates and reconciles files, troubleshoots database and data-integration issues, performs quality audits, maintains backups, and supports operational reporting. The analyst documents procedures, communicates data discrepancies and resolutions, assists with month-end processes, and helps improve standardized workflows while protecting confidential client information.

Coordinates data and process activities for a Managed Services Center, including ServiceNow CMDB reconciliation, data entry and validation, contract updates, quality assurance, task tracking, documentation, auditing, and business continuity support. Collaborates with internal teams and vendors to maintain accurate records, resolve discrepancies, and support ServiceNow operations. The role is remote and highly keyboard-intensive.

Analyzes supplier deal performance, revenue opportunities, forecasts, and commercial risks for global travel partnerships. Supports supplier negotiations, models deal structures, develops strategic reporting and optimization plans, and translates complex data into actionable recommendations for leadership, Sales, Pricing, and Client Management. The role requires strong analytical, commercial, communication, stakeholder engagement, and strategic thinking skills.

Build and maintain production data ingestion pipelines, transformation models, warehouses, and schemas for PerfectServe’s data platform. Deploy reliable, tested pipelines using idempotency and data-quality checks, apply dimensional and medallion modeling, participate in design reviews, and document owned pipelines and runbooks. The role requires SQL, programming experience, dbt or similar transformation tools, cloud data warehouse experience, ELT orchestration, AWS knowledge, and a strong data-testing mindset.

Analyzes institutional data, surveys, student success metrics, enrollment trends, academic information, and KPIs. Prepares internal and external reports, data visualizations, statistical analyses, and presentations supporting university planning, accreditation, strategic initiatives, grants, and program reviews. The role also provides survey design and data-analysis consulting to university departments and ensures data integrity.

Own end-to-end data workflows, including ingestion, storage, orchestration, transformation, validation, and delivery. Build ETL/ELT pipelines, manage cloud data platforms and transfers, optimize data models and queries, maintain data quality monitoring, troubleshoot production issues, and document data flows. Collaborate with technical and nontechnical teams to investigate discrepancies, support enterprise datasets, and apply secure data-handling practices.

Build and maintain finance data pipelines, warehouse models, dashboards, and automations for unit economics, technology budgeting, burn, runway, margins, deal desk, and sales compensation. Develop internal tools and LLM-based agents that help non-engineers access trusted financial data. Partner with finance, sales, and engineering leadership to reconcile discrepancies and improve revenue, cost, billing, payroll, cloud-spend, and accounting workflows.

Build and own customer-facing analyses, dashboards, and reusable reporting for ECP Insights. Conduct customer discovery, define reporting needs, write SQL and Python or PySpark in Databricks, contribute dbt models, validate accuracy, explain methodologies, and help prioritize the product roadmap. Collaborate with product, engineering, and customer-facing teams while handling HIPAA-protected health information.