Top Hybrid Data & Analytics Jobs in Los Angeles, CA

Lead Deals practice analytics by applying advanced analytics, visualization, and statistical modeling to extract insights, advise clients, drive business development, maintain executive client relationships, oversee multiple projects, ensure data integrity and security, promote innovative analytics technologies, and mentor analytics teams to deliver client growth and thought leadership.

Lead analytical studies to enhance Snap's SMC business, mentor a team of analysts, and develop data-driven strategies to inform growth and sales decisions.

The Log Specialist at Dynatrace leads log management initiatives, collaborates with sales, architects data ingestion solutions, and advocates for enhanced log consumption strategies.

As a Senior Forward Deployed Accountant, you will architect and automate accounting processes, engage with CFOs, troubleshoot technical issues, and drive AI-driven transformation across enterprise accounts.

The Analytics Engineer develops data models and KPIs, ensuring data reliability for decision-making while collaborating across multiple departments at Crexi.

The Sr. Analyst in Pricing Analytics drives data-driven strategies for GoodRx by analyzing pricing, collaborating with cross-functional teams, and developing dashboards to support business decisions.

The Staff Data Engineer will design and build data pipelines, reports, and tooling for the Concepts Lab, ensuring reliable AI systems and leading data modeling and analytics efforts. The role requires extensive experience in production data systems and collaboration across teams to transition concepts into production.

Lead strategic insights and ad measurement projects, analyze complex datasets, craft narratives connecting brand lift to business outcomes, partner with clients and cross-functional teams, and drive process improvements and customer-facing recommendations.

The Senior Data Engineer will design and optimize large-scale batch and streaming data pipelines using Scala and Spark, oversee the data engineering lifecycle, and engage in technical discussions to improve system efficiency.

Support analytics for a large multi-product client: implement measurement frameworks, run test-and-learn programs, validate data, analyze attribution/brand lift/MMM outputs, produce dashboards and actionable insights, and mentor analysts while coordinating with cross-functional and data partners.