Research Scientist, Central Applied Science (IC5)

Description

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.

Responsibilities

Work with vast amounts of data, generate research questions that push the state-of-the-art, and build data based 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 Communicate best practices in quantitative analysis to partners Work collaboratively with other scientists, engineers, UX researchers, and product managers to accomplish complex tasks that deliver demonstrable value Proactively identify, scope and implement innovative solutions with well defined intermediate milestones Actively identify new opportunities within Meta's long term roadmap for applied science contributions

Qualifications

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Currently holds a PhD in the field of Operations Research, Computer Science, or a related field At least 3 years of industry experience as an applied research scientist or a similar role 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 Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment Experience with large scale distributed AI training and inference 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 publications at leading journals or conferences such as ICML, NeurIPS, ICLR, IJCAI, AAAI, KDD, WWW, JMLR, JACM, MLSys or similar Experience with solving large-scale combinatorial optimization problems

Compensation: $74.04/hour to $217,000/year + bonus + equity + benefits