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Central Applied Science (CAS) 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.Central Applied Science is interdisciplinary, with expertise in computer science, statistics, machine learning, economics, political science, operations research, 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 to join the Product Algorithms team in Central Applied Science. The team is an interdisciplinary team of quantitative scientists that aims to deliver research and innovation that fundamentally increase the magnitude of Meta’s successes. The ideal candidate will have extensive graduate training in computer science, machine learning, statistics, operations research, or related disciplines, and the passion to solve real world hard scientific problems. By applying your expertise and passion you will be empowered to drive impact across a range of products, infrastructure and operational use cases at Meta.Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.

Research Scientist Intern, Product Algorithms (PhD) Responsibilities:

• 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.

Minimum Qualifications:

• Currently has, or is in the process of obtaining, a PhD degree in Computer Science, Statistics, Operations Research, or a related field.
• Experience analyzing datasets using languages like Python or R.
• Experience developing algorithms in languages like Python, C, C++ or Java.
• Experience with empirical research and for answering questions with data.
• 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 Qualifications:

• Expertise in one or more of the following fields: causal inference, machine learning, combinatorial optimization and stochastic modeling.
• Experience working with large-scale data systems, such as Presto, Spark, etc.
• 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, ICML, NeurIPS, AAAI, WWW, WSDM, etc.
• Experience working and communicating cross functionally in a team environment.
• Intent to return to degree-program after the completion of the internship/co-op.

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.