Top Remote Data & Analytics Jobs in Tucson, AZ

The Data Product Analyst designs and manages data products for insurance domains, ensuring they meet analytical and compliance standards while collaborating with cross-functional teams.

The Senior Data Analytics Engineer analyzes and delivers business intelligence solutions, builds data pipelines, and collaborates with clients to meet their data-driven needs.

The Strategy Analyst will provide financial analysis, lead internal reports, and recommend strategies for business growth, focusing on leveraging data.

Lead design and expansion of a unified analytics data platform integrating Medicare claims, clinical systems, and vendor feeds. Implement AI-augmented data engineering (LLM coding assistants, automated QA, autonomous data-quality agents), build validation/reconciliation/audit infrastructure, partner with analytics teams for reporting and modeling needs, and drive large-scale analytics platform and web app implementation while collaborating with IT on security and deployment standards.

Lead the design and implementation of analytics solutions, manage Adobe Analytics migrations, ensure data governance, and deliver cross-channel insights for customer journey optimization.

The Senior Analyst in Revenue Operations will manage planning cycles, headcount, performance plans, financial modeling, and collaborate with FP&A to support the GTM organization.

As a Senior Data Scientist, you will develop statistical models and machine learning algorithms to improve patient enrollment and trial management while ensuring compliance in a healthcare data environment.

The job involves leveraging AWS and Snowflake for data engineering tasks within a technology-focused company, requiring US residency.

As a Data Science Intern, you'll learn to translate business challenges into statistical problems, analyze large datasets, build machine learning models, and communicate insights effectively.

The Senior Data Engineer will design and build scalable data platforms, handle automation for data operations, and ensure reliability and performance of data pipelines while collaborating with various teams.