Research Scientist Manager — Statistics and Privacy, Marketing Science R&D

Marketing Science R&D focuses on establishing step-change improvements to the efficiency of marketing on our platform. The team's expertise spans domains including causal inference, survey methodology, machine learning, cryptography, neuroscience and record linkage. We develop methodologies, design and prototype solutions, and partner with our engineering and product colleagues to scale these solutions such that millions of advertisers can benefit.

This managerial role encompasses leading and supporting a high-performing research science team focused on statistics and privacy, as well as broader org responsibilities. This will entail building scientifically rigorous systems focused on optimizing for causal advertising outcomes, while also adopting new model training approaches that facilitate technological guarantees of consumer privacy.

This position is full-time and is based in London.


  • Hire and lead highly skilled research scientists, providing mentorship and career guidance to members of the team
  • Foster innovation and prioritize across specific opportunities to build new and improve existing causal inference systems for ads delivery optimization
  • Shepherd the team's research and development projects, ensuring high-quality communication across diverse audiences, and taking responsibility for the team's long-term product impact
  • Build cross-functional relationships with Engineering, Product and Analytics teams to shape long-term roadmaps with a balance of scientific rigor and strategic considerations
  • Manage the development of conference presentations, patent applications, white papers and publications that are broadly appealing and accessible beyond a core scientific audience
  • PhD in a quantitative field such as statistics, physics, economics or political science and 3+ years of relevant experience in data science or research science, or MS degree with 7+ years of relevant experience in data science or research science
  • 2+ years of product development experience
  • 2+ years of experience in leading and developing scientific teams, including performance management and recruiting
  • Strong command of R, Python or Julia leveraging large (TB) datasets
  • Expertise in causal inference and experimentation, including addressing challenges from incomplete, unrepresentative, mislabeled and observational data
  • Proven track record of innovation and strategic focus
  • Understanding of privacy-related technologies and frameworks such as multi-party computation, differential privacy, federated learning, and homomorphic encryption
  • Experience with probabilistic programming languages such as Stan
  • Proficiency with modern machine learning techniques and understanding of their mathematical underpinning
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