Currently has, or is in the process of obtaining, a PhD degree in a quantitative field such as Statistics, Computer Science, Information Science, Economics, Operations Research, Data Science, Quantitative Marketing or relevant technical field Experience in machine learning and statistical research covering at least one of the following domains: statistical modeling, behavioral modeling, economics, model evaluation or generative AI 1+ years in programming, analysis, and visualization using computing software and libraries such as Python or R Interpersonal experience: cross-group and cross-culture collaboration Experience in scalable dataset assembly/data wrangling, such as Hive, Spark or Presto Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment Intent to return to degree-program after the completion of the internship/co-op Proven track record of achieving significant results as demonstrated by previous internships or industry experience, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as KDD, The Web, AI STATS, AAAI, NeurIPS, ICML, EC, or similar Experience working and communicating cross functionally in a team environment Availability for sixteen (16) weeks or moreMeta builds technologies that help people connect, find communities, and grow businesses. The team works closely with various product groups throughout Meta, bringing expertise in anomaly detection, bayesian modeling, bias correction, model evaluation, synthetic population, behavioral modeling and pricing, and applying them for various applications.