Top Data & Analytics Jobs in Tucson, AZ

The role involves collecting, analyzing, and visualizing data for investment research, utilizing web scraping, data tools, and data science techniques.

Develop and maintain datasets for visualization and machine learning; automate data pipelines; partner with teams to build data products.

The Data Analyst role involves collecting, analyzing, and interpreting program data to support decisions and reporting, while ensuring data accuracy and security. Responsibilities include developing dashboards, identifying trends, and collaborating with teams.

The role involves leading e-commerce strategies, conducting analysis and A/B testing, collaborating across teams to optimize performance, and translating insights into actionable plans for clients.

Identify, develop, and deploy automated cost-saving audits using complex SQL against claims data. Build and maintain financial and ad-hoc reports, run medical record review and administrative hold concepts, lead cross-functional discussions, train teammates on SQL, triage operational tasks (Salesforce, audit letters, reimbursements), and partner with data/engineering to resolve data issues affecting payment integrity.

Lead a data science team to develop insights from autonomous vehicle data, create scalable platforms for data access, and collaborate with cross-functional teams on performance measures.

The Senior Director, Epidemiology leads epidemiology strategies and activities for Revolution Medicines, including developing plans, overseeing deliverables, and collaborating on clinical development and safety aspects.

The Senior Data Engineer will design, implement, and optimize scalable data solutions, working with data pipelines and collaborating with cross-functional teams in healthcare.

The EDI Growth Specialist at Alvys focuses on creating and maintaining EDI data mappings, translating various data formats, collaborating with team members, and validating mappings for EDI integrations.

Design, build, and maintain scalable, reliable data pipelines and services. Write well-tested Python and SQL code, work with orchestration (Airflow), containers, and cloud infrastructure. Collaborate cross-functionally to deliver data products and improve development processes.