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Zeta Global

Data Scientist

5w

Zeta Global

Copenhagen, DK · Full-time · DKK 450,000 – DKK 550,000

About this role

Zeta Global is seeking a motivated and curious Data Scientist to join the Machine Learning team in Copenhagen, working within the Agentic DSP pod. This entry-level role focuses on designing, analyzing, and improving machine learning models for a large-scale, real-time advertising platform.

You will analyze large datasets to extract insights, contribute to model design and evaluation, and collaborate with software engineers to bring models into production. The work involves experimentation, prototyping, and iterative improvement of probability prediction models using deep learning and AI agents.

The Copenhagen office is one of the company's strongest engineering hubs, bringing together highly skilled 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, and you will collaborate with global teams in San Francisco, New York, Berlin, and Prague.

This role offers the chance to learn how real-world ML systems are built, deployed, and maintained at scale. You will work alongside experienced engineers and scientists, exploring modern ML/AI techniques to develop cutting-edge systems powering the AI-driven advertising platform.

Requirements

  • Strong academic background in Physics, Mathematics, Computer Science, or a related quantitative field
  • Solid understanding of mathematics, statistics, or algorithms
  • Basic knowledge of machine learning and AI
  • Experience with software engineering principles (through studies, projects, or internships)
  • Experience programming in Python
  • Curiosity, self-motivation, and a willingness to learn

Responsibilities

  • Analyze large datasets to extract insights and support model development
  • Contribute to the design and evaluation of machine learning models
  • Work closely with software engineers to bring models into production
  • Participate in experimentation, prototyping, and iterative improvement
  • Learn how real-world ML systems are built, deployed, and maintained at scale
  • Explore and apply modern ML/AI techniques, including deep learning and AI agents, to develop and improve cutting-edge probability prediction models in a real-time DSP environment