Top Data & Analytics Jobs in Sacramento, CA

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 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.

The Senior Analyst will support product engineering efforts by analyzing digital solutions, enhancing user experiences, and collaborating across teams to deliver insights and improvements.

Provide technical and administrative support to leadership: monitor sprints and Scrum synchronizations, perform technical research, write Python scripts for automation and API testing, manage and report data using advanced Excel, and prepare meeting summaries and cross-functional coordination.

Lead analytics and insights for the CFO and exec team: produce executive-ready analyses, design scalable analytics infrastructure, leverage AI to accelerate workflows, partner cross-functionally to drive strategy and execution, and manage multiple high-impact initiatives.

Lead a team of data engineers to design, build, and maintain scalable data pipelines, a Data Vault, data warehouses and marts. Own backlog, sprint planning, mentoring, stakeholder collaboration, data validation/monitoring, and platform improvements to deliver key metrics and data infrastructure across the business.