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 and pursue research questions that push the state-of-the-art, and build science-driven products.
• Develop novel quantitative methods on top of Meta's unparalleled data infrastructure.
• Work systematically and make consistent progress towards long-term ambitious, research goals.
• 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 scientific contributions.

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• PhD in Computer Science, Statistics, Operations Research, Economics, or a related technical field.
• 2+ years of work experience developing and deploying scientific algorithms at large scale.
• 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, ambiguous problems and evaluating alternative solutions, tradeoffs, and diverse points of view.
• Experience working and communicating cross functionally, in a rapidly changing 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.