Requirements

Currently has or is in the final stages of obtaining a PhD in the field of Computer Science, Data Science, or a related field, or equivalent practical experience. Degree must be completed prior to joining Meta.
Experience with empirical research and for answering questions with data.
Experience developing algorithms in languages like Python, C, C++ or Java.
Experience analyzing datasets using languages like Python or R.
Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment.

Nice to Haves

Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.
Experience working and communicating cross functionally in a team environment.
Experience analyzing large datasets using tools like Presto, Hive or Spark.
Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops, journals or conferences such as KDD, ICML, NeurIPS, COLT, EC, IJCAI, AAAI, TheWebConf, STOC, FOCS, SODA, Operation Research or similar.

Work with vast amounts of data, generate research questions that push the state-of-the-art, and build data-driven products.
Develop novel quantitative methods on top of Meta's unparalleled data infrastructure.
Learn new tools, systems, and programming languages quickly as required by the particular project you are working on.
Work towards long-term ambitious research goals, while identifying intermediate milestones.
Communicate best practices in quantitative analysis to partners.
Work both independently and collaboratively with other scientists, engineers, UX researchers, and product managers to accomplish complex tasks that deliver demonstrable value.
Publish research results in top-tier conferences and at leading journals.
Actively identify new opportunities within Meta's long term roadmap for applied science contributions.

Meta is committed to providing reasonable support (called accommodations) in recruiting processes for candidates with disabilities, long-term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support.