Top Remote Data & Analytics Jobs in Phoenix, AZ

Build and maintain production-grade data processing systems and foundational infrastructure for enterprise AI. Collaborate with researchers and engineers, deliver end-to-end implementations, transform unstructured data into performant datasets, and use distributed processing frameworks and modern analytics tooling to inform products and strategy.

The Analytics Manager analyzes complex datasets, builds models, conducts scenario analyses, and provides strategic recommendations to guide decision-making for leadership.

The Actuarial Specialist produces analyses, manages projects, and oversees team workload to enhance actuarial processes in the organization, ensuring business growth and profitability.

The Data & Analytics Architect will design and implement analytics solutions, support client engagements, and lead data architecture projects, requiring extensive technical and consulting skills.

As a Machine Learning Engineer, you'll develop and deploy ML models for medical imaging, collaborate with teams, and optimize for production environments.

As a Data Engineering Architect, lead the transformation of data engineering into a modern platform, oversee architecture and technical leadership, design scalable systems, ensure data quality and governance, and mentor teams for a data-driven culture.

The role involves administering Salesforce, developing automations with Flows and Apex, and maintaining data pipelines to support revenue operations at ElevenLabs.

The Principal Data Engineer will lead data architecture initiatives, design scalable data systems, and oversee data standards across teams while ensuring high-quality data infrastructure and guiding engineering teams.

Analyze conversational call flows and large datasets to optimize IVR and generative AI systems. Perform call testing, annotation, dashboard monitoring, and deliver data-driven insights and presentations to improve self-service, reduce agent handling, and enhance customer experience.

Design, build, and maintain an internal data platform and pipelines. Ensure secure, governed, resilient data access for engineering and BI teams. Partner with architects, implement automations, support platform consumption, mentor users, and drive continuous improvement and compliance.