Top Hybrid Data Science Jobs in Los Angeles, CA
Support and assist a team of scientists and engineers in developing novel semiconductor integration processes for electronics applications, including RF electrical performance, thermal-mechanical constraints, chemical/metallurgical issues. Conduct theory-driven analyses, research projects, and maintain vendor relationships. Must have MS or Ph.D. in Material Science, Physics, Physical Chemistry. Proficiency in semiconductor manufacturing processes and packaging technology, design of experiments, and Microsoft Office tools.
Looking for a Senior Machine Learning Scientist to develop new machine learning products for a real-time acquisition marketing platform. Responsibilities include hands-on development of scalable algorithms, keeping up with latest ML advancements, and contributing to the company's ML roadmap.
Join Snap Inc as a Data Scientist and apply quantitative analysis, data mining, and statistical modeling to deliver impactful insights for informed business and product decisions. Collaborate with cross-functional teams to optimize product performance and drive projects to completion.
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The Senior Data Scientist at Sensor Tower will leverage digital advertising and industry knowledge to drive strategies that improve the accuracy and offerings for our Digital Marketing insights solution. The role involves developing data modeling algorithms, working on AI projects, and acting as a subject matter expert for digital advertising.
Join Warner Bros. Discovery as a Data Scientist II to support the Max marketing teams in understanding the impact of marketing on sales, profitability, and brand equity. Develop and maintain market mix models, analyze media spend performances, and optimize media spend to maximize subscriber growth and revenue. Must have expertise in SQL, R, Python, and Databricks with 3+ years of experience in data science and statistical modeling.
Lead Data Scientist working closely with cyber SMEs and business stakeholders to produce a holistic cyber risk view across the enterprise. Responsibilities include leading data analytics processes, managing cyber metrics program, and analyzing data to share insights with peers.
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