Top Data & Analytics Jobs in Los Angeles, CA

The Business Solutions Analyst collaborates with stakeholders to analyze and enhance technology solutions within Film & TV marketing, focusing on Digital Asset Management and marketing processes.

The role involves leading audience insights research supporting programming strategy, analysis of customer loyalty, and strategic product planning. It requires data analysis expertise to inform business decisions and enhance audience engagement.

The Data Scientist will develop end-to-end models using automated data pipelines, evaluate business opportunities, and collaborate with teams for optimization tests.

The Manager, Portfolio Strategy is responsible for managing a team, developing monitoring frameworks, analyzing portfolio performance, and presenting insights to optimize profitability and risk for a billion-dollar portfolio.

The Senior Analyst will provide insights to drive business growth, assess portfolio risks, and implement pricing strategies while collaborating with various teams.

The Data Systems Manager will oversee data architecture, implement MDM strategies, ensure data quality, and drive governance initiatives to support business intelligence.

Lead Statistical Programmer responsible for developing SAS programs for clinical trial data analysis. Collaborate with teams, ensuring compliance and quality standards. Mentor junior programmers.

As a Machine Learning Engineer, you'll enhance ML productivity, improve model deployment, and implement algorithms for credit decisioning systems.

As a Lead Data Architect, you'll design enterprise-grade data platforms, ensuring compliance, scalability, and guiding teams in data modeling and governance.

The Principal Credit Risk Analyst leads credit risk evaluation, monitoring, and optimization for lending portfolios, collaborating with cross-functional teams to drive informed growth and ensure compliance with regulatory standards.

The Business Intelligence Engineering Manager will lead an analytics team, drive insights, manage operations, and optimize data models while collaborating across departments and ensuring data quality and governance.