Zeta Global
Marketing Technology
DataScientist
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“Data Scientist at Zeta Global”
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Full Job Description
WHO WE ARE Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com. The Role Zeta Global is looking for a motivated and curious Data Scientist to join our Machine Learning team in Copenhagen, working within the Agentic DSP pod. Our Copenhagen office is one of the strongest engineering hubs in the company, bringing together a highly skilled group of engineers, data scientists, and researchers with backgrounds in Physics, Mathematics, and Computer Science. The environment combines deep technical expertise with a pragmatic, product-focused mindset. You will collaborate closely with our global teams across San Francisco, New York, Berlin, and Prague, contributing to the development of next-generation machine learning systems powering our AI-driven advertising platform. As a Data Scientist, you will work alongside experienced engineers and scientists to design, analyze, and improve machine learning models used in a large-scale, real-time system. This is an entry-level role, and we do not require prior industry experience. Instead, we are looking for strong fundamentals, intellectual curiosity, and a willingness to learn. Key Responsibilities: Analyze large datasets to extract i
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