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Data Science Intern (PhD) (Summer 2024)

The Data Science & Analytics organization's mission is to increase our speed, frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering, product analytics, causal inference, economics, statistical modeling and machine learning. Aligned and partnering with product verticals, we use this extensive toolbelt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure impact on our community of players and developers.


Your Role:

  • Collaborate with data scientists and engineers to research and develop advanced data analytics, causal inference and machine learning solutions to power the business and product innovations.
  • Conduct in-depth research to address complex data-related challenges.
  • Work on projects that have a real impact on our products, services, and business strategy.
  • Apply your work to expedite product innovations, including in-experience experiments, friend recommendations, and dynamic resource allocation for experience servers
  • Present your findings and recommendations to both technical and non-technical stakeholders.


  • PhD candidate (completing at least the third year) in a quantitative field such as Statistics, Computer Science, Economics, or Computational Social Science.
  • At Least 1 year of experience doing causal inference or deep learning or reinforcement learning via research or prior internship.
  • High proficiency in SQL, Python or R
  • Proficiency in big data query/processing languages and tools such as SQL, Hive, Spark, or Airflow.
  • Familiarity with algorithmic scalability, including numeric approximation and sketching.
  • Passion for applying scientific rigor to advance dynamic consumer products.
  • Willingness to work full-time and onsite in San Mateo, CA.
  • Experience in developing production solutions is a plus.