Top Remote Entry Level Data & Analytics Jobs in CO

Monitor prediction markets and perpetual futures by tracking news, trader sentiment, venues, volumes, open interest, funding rates, and market share. Research protocols and users, build dashboards and datasets, identify product opportunities for Pyth, size opportunities with market and on-chain data, and collaborate with product, engineering, and business development teams. Write research reports, present recommendations to leadership, and evaluate launched initiatives against their original theses.

Support Sales and Key Account teams by owning trade performance reporting, building dashboards, analysing promotional ROI, preparing category presentations for range reviews, and collaborating with Marketing, Supply Chain, and Finance to drive commercial decisions.

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.

Develops and maintains Power BI dashboards and data models, defines KPIs with stakeholders, validates data accuracy, and collaborates with Data Engineering on optimized analytical models. The role documents data lineage and reporting assumptions, supports self-service BI through communications and training, and automates manual reporting processes. It requires SQL, Power BI, DAX, Power Query, data modeling, and data warehouse knowledge, plus strong communication and cross-functional collaboration skills.

Supports the Mortgage Lending Division by producing and maintaining routine reports, dashboards, data extracts, and basic analyses. Validates data accuracy, automates reporting where appropriate, documents procedures, investigates trends and audit issues, and responds to operational reporting needs. The role involves learning internal systems, metrics, and business processes while collaborating with stakeholders. Candidates should have basic Excel and data visualization skills, foundational SQL knowledge, strong analytical abilities, and zero to two years of relevant experience.

Supports the Mortgage Lending Division by producing and maintaining routine reports, dashboards, data extracts, and ad-hoc analyses. Validates data accuracy, documents reporting procedures, investigates trends and audit issues, and collaborates with business teams to understand performance metrics and reporting needs. The role requires basic Excel and data visualization skills, foundational SQL knowledge, attention to detail, and a willingness to learn internal systems and processes.