We are looking for researchers and applied scientists to join the Central Applied Science team. Central Applied Science is an interdisciplinary team of quantitative scientists that aims to deliver research and innovation that fundamentally contribute to Meta's success. By applying your expertise in quantitative methods, you will be empowered to drive impact across a range of products, infrastructure and company operations. Individuals in this role are expected to have expertise and publications within research areas including artificial intelligence, machine learning, statistics, causal inference and experimentation. The ideal candidate will have a passion for building data-driven products and forming research frameworks to solve challenging, real-world problems.

• 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.
• 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.
• Actively identify new opportunities within Meta's long term roadmap for data science contributions.

• Currently has or is in the process of obtaining a PhD in the field of Computer Science, Statistics, Operations Research, or a related field, or equivalent practical experience. Degree must be completed prior to joining Meta.
• Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical 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.

• 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, EC, ICML, NeurIPS, or similar.