Top Big Data Jobs in Los Angeles, CA

The General Manager, Lead Generation will launch a new lead generation business, creating strategy, operations, and team from the ground up to drive profitability.

The Senior Growth Strategist will drive growth for early-stage products, managing campaigns, analyzing data, and experimenting with creative strategies.

The Lead Growth Strategist will develop and implement innovative, data-driven marketing strategies to grow Startpage's user base and increase app installations and browser usage.

As a Senior Software Engineer in Release Infrastructure, you will enhance developer efficiency, own critical systems, and shape internal platform vision.

The Account Manager, Client Success, oversees DSP accounts, optimizes media performance, collaborates with Sales, and manages relationships to drive growth.

Field inbound member and provider calls for assessment, triage, and crisis management; focus on inpatient psychiatric and chemical dependency admissions; determine medical necessity and levels of care; manage inpatient cases through treatment, consult facility staff, and identify needed clinical services. Attend compliance training and team meetings.

As a Data Engineer, you will design and maintain scalable data pipelines, collaborate with teams to improve data solutions, and ensure data quality for DISQO's ad measurement platform.

The VP of Global Channels will lead Nasuni's channel sales strategy, market expansion, partner recruitment, and team leadership to drive revenue growth through indirect sales channels.

The Senior Site Reliability Engineer will support, maintain and grow the Atlas platform, focusing on automating processes and running multi-cloud environments.

Join the Data Science Team at Edmunds to design and implement AI-driven initiatives, optimize products, and collaborate with engineers and product managers in the development of ML solutions.

As a Sr. Full-Stack Engineer, you will lead development initiatives, mentor junior developers, design scalable applications, and drive system architecture, ensuring high-impact solutions.

Build and own full-stack UX and backend systems for the ML lifecycle: design architecture, integrations, observability, CI/CD, and production frontend/backends. Lead technical initiatives, mentor engineers, and collaborate across teams to scale ML platform capabilities.