Top Analysis Reporting Jobs in Tucson, AZ

In this role, you will lead deal analytics efforts, providing data-driven insights for strategic decisions, manage client relationships, and develop junior team members while participating in business development activities.

Support cross-functional teams by driving data-driven decisions: design and analyze A/B tests, leverage ML models for insights, define growth levers, and automate operational processes to scale customer acquisition and partnerships.

Review and label Japanese-language text, images, or videos for AI projects; flag factual errors, sensitive or inappropriate content; follow guidelines and ask clarifying questions as needed.

Senior domain expert responsible for translating payment integrity domain knowledge (CR, COB, DM) into scalable rule logic, workflows, automation, and AI-enabled solutions. Partners with product, engineering, analytics, and operations to design, govern, and continuously improve rules, orchestration, and automation to reduce false positives and prevent improper payments.

Own revenue analytics and reporting infrastructure to drive go-to-market efficiency. Build and maintain dashboards, ensure data accuracy across the revenue tech stack, perform cohort analyses and forecasting, automate reporting, analyze distribution productivity, pipeline health, and onboarding efficiency, and collaborate with finance on revenue recognition and bookings reconciliation.

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.

Build and maintain Databricks-based ETL/ELT pipelines, transform and model data, optimize workflows, monitor and troubleshoot pipelines, and collaborate with cross-functional teams.

Collaborate with research scientists to perform applied psychometric analyses on Exact Path adaptive assessments, prepare and analyze large datasets, modify and write R code, interpret findings, update technical documentation, and design studies to improve assessment reliability, validity, and fairness.

Design and manage curated fact and dimension datasets, semantic/subject-area models, and governance. Partner with BI and data engineering to enable self-service analytics, ensure data quality and documentation, and prepare datasets to support future ML and advanced analytics.

Lead the Cloud Operations team to ensure high availability, scalability, and security of multi-tenant and hosted products. Drive automation, incident management, and collaborate cross-functionally for cloud solutions.