Top Hybrid Data & Analytics Jobs in Los Angeles, CA

The Sr. Specialist, Business Intelligence Engineer analyzes data to aid business decisions, optimizes performance, builds dashboards, and collaborates with teams to drive revenue insights.

Intern will design and execute quantitative analyses, build reporting tools, conduct revenue analyses, and learn about the ad tech industry while collaborating cross-functionally.

As a Staff Data Engineer, you will lead data engineering initiatives, architect and build scalable data pipelines, and mentor teams, enhancing Crunchyroll's data infrastructure within AWS and GCP environments.

Manage projects and teams to leverage data and technology in M&A, driving strategic insights and improving deal decisions through advanced analytics and AI.

As a Data Engineer Intern, you'll develop and maintain data pipelines, support ETL processes, analyze data, and complete a capstone project, while learning from experienced mentors.

This role involves analyzing complex datasets, generating insights, building dashboards, and supporting analytics initiatives within Universal Entertainment's Film and TV sectors.

The Associate Director, Biostatistics is responsible for statistical guidance in clinical study design, data analysis, and regulatory submissions, leading clinical study teams to ensure timely and quality outcomes.

Responsible for leading the MDM strategy, ensuring data accuracy and consistency, designing MDM lifecycles, and mentoring a team of data stewards.

Lead the strategy and governance for enterprise-wide data quality initiatives, ensuring data accuracy and regulatory compliance while managing a high-performing team.

The Strategic Research Lead will act as the primary contact for market research clients, manage research projects, ensure client satisfaction, and deliver actionable insights based on data analysis.

Support RevOps by building and maintaining dashboards, ensuring revenue data accuracy, preparing executive and Board reporting, conducting ad hoc analyses, identifying data quality issues, and communicating insights to technical and non-technical stakeholders.