Top Hybrid Senior Level Data & Analytics Jobs in CO

As a Senior Analyst, you'll gather and analyze requirements, implement process improvements, manage financial reporting in Workday, and mentor junior analysts.

The AV Safety Analytics Engineer will develop data analytics infrastructure for automated vehicle safety, utilizing cloud processing and statistical methods. Responsibilities include creating data visualizations, monitoring metrics, and ensuring data integrity across systems.

As a Staff Data Engineer, lead the technical roadmap for data infrastructure, manage complex data architectures, and mentor engineers while driving the organization's data platform innovations.

The Senior Data & Analytics Consultant will lead data structuring, reporting, and analysis for the pet business, ensuring accurate reporting to meet business objectives.

The Cloud Data Architect will design and implement data architecture solutions within a SaaS environment, ensuring data security and efficiency while leading technical standards and collaborative teams.

The EIR Analyst conducts rigorous evaluation and research using the Colorado All Payer Claims Database, translating findings into actionable insights to improve healthcare in Colorado through innovation and data-driven solutions.

Lead fraud detection efforts by analyzing data, developing detection methods, collaborating with teams, optimizing fraud rules, and monitoring performance metrics.

The Senior Portfolio Lead will oversee data management services for clients, ensuring quality deliverables, strategic oversight, and optimal clinical data flows, while leading cross-functional teams and managing complex client relationships.

The role involves assessing fraud program effectiveness, compliance with regulations, and providing strategic insights for risk management within the financial services industry.

Lead design and implementation of scalable, HIPAA-compliant data pipelines and platforms for healthcare ML. Build ETL, orchestration, and tooling for processing EHR, claims, pharmacy, and bioinformatics data; collaborate with data scientists to produce modeling-ready datasets and ensure data quality, reliability, and operational excellence.