Research Scientist Intern, Central Applied Science (PhD)
About The Position
Central Applied Science (CAS) is Meta’s interdisciplinary research and development team, focused on strategic projects that combine research and engineering. The team applies scientific rigor, methodological innovation, and engineering to create real-world impact. Its expertise spans areas including computer science, statistics, machine learning, economics, political science, operations research, marketing science, and sociology. CAS collaborates with Meta product groups and the academic community, and builds and open-sources technical products aligned with its areas of expertise. The team seeks PhD research interns with expertise in areas such as statistical modeling, economics, experimentation, game theory, and generative AI modeling and evaluation. CAS applies expertise in anomaly detection, Bayesian modeling, bias correction, model evaluation, synthetic populations, behavioral modeling, and pricing to product applications. Its work addresses critical problems that help Meta make robust and trustworthy strategic decisions and build products that serve and protect users. Internships last 12 to 24 weeks, with various start dates throughout the year.
Requirements
- Currently have or be pursuing a PhD in a quantitative field such as Statistics, Computer Science, Information Science, Economics, Operations Research, Data Science, Quantitative Marketing, or a relevant technical field.
- Experience in machine learning and statistical research in at least one of the following areas: statistical modeling, behavioral modeling, economics, model evaluation, or generative AI.
- At least 1 year of programming, analysis, and visualization experience using computing software and libraries such as Python or R.
- Experience collaborating across groups and cultures.
- Experience with scalable dataset assembly or data wrangling using tools such as Hive, Spark, or Presto.
- Must obtain work authorization in the country of employment by the time of hire and maintain work authorization during employment.
Nice To Haves
- Intent to return to a degree program after completing the internship or co-op.
- A demonstrated record of significant results through previous internships or industry experience, fellowships, patents, or first-authored publications at leading workshops or conferences such as KDD, The Web, AI STATS, AAAI, NeurIPS, ICML, or EC, or similar venues.
- Experience working and communicating cross-functionally in a team environment.
- Availability for 16 weeks or more.
Responsibilities
- Build pragmatic, scalable, and statistically rigorous solutions to critical inferential and decision problems, using or developing state-of-the-art statistical and machine learning methodologies on Meta’s data infrastructure.
- Use strong communication skills to develop cross-functional partnerships and share statistical best practices throughout the company.
- Work independently and collaboratively with scientists, engineers, designers, UX researchers, and product managers on complex tasks that deliver demonstrable value to Meta’s community.
- Identify opportunities for data-scientific contributions to Meta’s long-term roadmap through creative, proactive, and forward-looking thinking.
Benefits
- Benefits are offered; specific benefits are not listed.
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What This Job Offers
Job Type
Full-time
Career Level
Intern
Education Level
Ph.D. or professional degree
