Research Scientist Intern, Graph Science and Statistics Research (PhD)

Core Data Science (CDS) is a research and development team, working to improve Meta’s products, infrastructure, and processes. We generate real-world impact through a combination of scientific rigor and methodological innovation. Our focus is on longer-term, foundational work that addresses new opportunities and challenges across the Meta family of apps. The work we do enhances the Meta family of apps that enable billions of people to communicate with each other daily. Core Data Science is interdisciplinary, with expertise in computer science, statistics, machine learning, economics, political science, operations research, marketing science and sociology, among many other fields. This diversity of perspectives enriches our research and expands the scope and scale of projects we can address. We deliver value through collaborative projects with other groups at Meta and with the academic community. In addition, we build and open-source technical products aligned with our areas of expertise. We are looking for research interns with expertise in statistical inference, representation learning or network science. The team works closely with various product groups throughout Meta, bringing expertise in modeling, statistical methodology, model evaluation, representation learning, network science, and social network analysis. We solve critical problems that enable Meta to make robust and trustworthy strategic decisions and build products that best serve and protect their users.

Required Skills

Research Scientist Intern, Graph Science and Statistics Research (PhD) Responsibilities:

• Build pragmatic, scalable, and statistically rigorous solutions to mission critical inferential and decision problems by leveraging or developing state of the art statistical and machine learning methodologies on top of Meta’s unparalleled data infrastructure.
• Apply excellent communication skills in order to develop cross-functional partnerships throughout the company and spread statistical best practices.
• Be able to work both independently and collaboratively with other scientists, engineers, designers, UX researchers, and product managers to accomplish complex tasks that deliver demonstrable value to Meta’s community of over 3.5 billion users.
• Think creatively, proactively, and futuristically to identify new opportunities within Meta’s long term roadmap for data-scientific contributions.

Minumum Qualification

Minimum Qualifications:

• Currently has, or is in the process of obtaining, a PhD in a quantitative field such as but not limited to Statistics, Computer Science, Data Science or similar
• Experience in machine learning and statistical research covering at least one of the following domains: graph and sequence modeling, statistical modeling, network science, marketing science, relational learning, user modeling, model evaluation or active learning
• 1+ years in programming, analysis, and visualization using computing software and libraries such as Python or R
• Experience in scalable dataset assembly/data wrangling, such as Hive, Spark or Presto
• Interpersonal experience: cross-group and cross-culture collaboration
• Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment

Preferred Qualification

Preferred Qualifications:

• Intent to return to degree-program after the completion of the internship/co-op
• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as KDD, The Web, AI STATS, AAAI.