Top Data & Analytics Jobs in Sacramento, CA

Lead analytics strategy for a financial institution, ensuring compliance and driving marketing analytics through predictive modeling and team management.

Lead CX analytics strategy and operations by standardizing metrics, enabling self-service analytics, and embedding AI in the analytics lifecycle to enhance decision-making processes.

Manage analytical service operations by overseeing a team, designing software for data mining, developing statistical models, and generating insights for marketing outcomes. Provide training and mentorship to direct reports.

Lead the evolution of data platform by designing scalable pipelines, improving data processes, mentoring teams, and modernizing data architecture.

The Senior Product Data Analyst will lead product analytics, conduct deep-dive analyses, drive product decisions, communicate insights, and enhance analytics best practices at Mixbook.

As a Data Engineer II, you will build and optimize data pipelines in Databricks, ensure high-quality data delivery, and support generative AI applications. You will collaborate with data scientists and AI engineers to provide reliable data infrastructures and meet business needs.

The GRC Content & Strategy Sr. Associate will design and maintain GRC content, develop documentation, provide platforms expertise, and conduct research on GRC trends.

As a Lead Product Data Analyst, you'll drive data-informed decision-making across teams, develop data products, collaborate on metrics, and influence product strategies.

Lead and grow a casino analytics team to measure, diagnose, and optimize Casino revenue performance. Provide strategic analytics support to Revenue Operations, run deep-dive customer and promotion analyses, build scalable monitoring/alerting frameworks, translate insights into actionable recommendations, and manage an analytics roadmap prioritizing short-term wins and long-term AI-enabled strategies.

Support sales intelligence by collecting, preparing, and analyzing sales and marketing data; maintain dashboards and data quality; run pipeline and win/loss analyses; translate findings into clear visualizations and reports for stakeholders.