Top Remote Data & Analytics Jobs in Denver & Boulder, CO

Own fraud detection and mitigation for ACH payments: design controls, run investigations, analyze performance (precision/recall, financial impact), and partner with Product, Data Science, Risk ML, and Engineering to operationalize risk strategies and transition to model-driven controls.

Lead Finance Data & Analytics to build trusted data sources, governance, and analytics for Finance and cross-functional stakeholders. Manage analysts, drive data strategy and Snowflake data models, produce insights via SQL and Tableau, and deploy AI solutions to optimize finance decision-making and operations.

Lead strategic vision and execution of GitLab's data platform and analytics capabilities, focusing on AI-enabled self-service analytics and data governance.

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.

Implement, configure, and test decision engine process flows and rule changes. Execute QA, A/B tests, and historical backtesting. Validate data integrity between vendors and core apps. Gather requirements, document processes, and collaborate with Pricing, Risk, and Engineering to ensure accurate, efficient decisioning.

Own and evolve the data infrastructure powering identity and fraud products. Build and operate scalable ETL/ELT pipelines, ensure data quality and observability, optimize storage and access, support product squads, respond to production incidents, mentor engineers, and drive data platform innovation.

Lead the Data Platform Engineering team owning ETL/reverse-ETL pipelines, replication, and production datastores. Define architecture, roadmap, standards (IaC, observability, schema contracts), mentor engineers, drive incident response and durable fixes, and partner on cross-team technical decisions and operational reliability for data correctness, completeness, and timeliness.

Lead architecture and implementation of scalable batch and streaming ETL/ELT pipelines, data services, and graph-serving models for Observability & Insights. Own technical strategy, drive performance and cost improvements, enforce data governance and observability, lead cross-team initiatives, participate in on-call and incident follow-through, and partner with product and engineering to deliver low-latency graph exploration at extreme scale.

Lead revenue-cycle performance analyses, diagnose root causes, quantify value (ROI/collections lift), and translate findings into pragmatic, stakeholder-ready recommendations. Partner cross-functionally to scope analyses, validate data, and drive strategic workstreams that inform product roadmap and client outcomes.

Lead analytics engineering for Revenue, Marketing, and Finance by building scalable data solutions, data models, and dashboards; provide training and consultation, support ad hoc data needs, and translate technical findings into executive-level insights to improve operational performance.