Research Scientist Intern, Auction & Delivery Research (PhD)
Meta

Job Info

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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, 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 Auction & Delivery team in Core Data Science. The massive scale and heavy engagement of the people using our products make our Family of Apps an ideal place for marketers to build their brands. It also makes the platform an ideal place to conduct analyses and research to learn how to improve digital marketing. The successful candidate will focus on coming up with novel approaches to improve both advertiser as well as user value we drive from our ads system. The team is both theoretical and practical as we work with product engineers and with our top tier advertisers to build our understanding and to test ideas. The ideal candidate will have extensive graduate training in computer science, data science, machine learning, or related disciplines, and an interest in answering challenging, open-ended research questions with real-world impact. Expertise in one or more of the following categories is preferred but not required: -reinforcement learning; operations research.-automated machine learning Our internships are twelve (12) - twenty four (24) weeks long and have various start dates throughout the year.

Research Scientist Intern, Auction & Delivery Research (PhD) Responsibilities:

• Answer important product and business questions, by applying appropriate scientific methodologies, and developing new methodologies when necessary
• Identify new areas across the family of Meta apps and products where economic, statistical or algorithmic insights can drive product improvements.
• Synthesize and apply insights from the relevant academic literatures to Meta's products.
• Work both independently and collaboratively with other scientists, engineers, designers, UX researchers, and product managers to accomplish complex tasks that create value for Meta's community of over 2 billion users.

Minimum Qualifications:

• Currently has, or is in the process of obtaining, a PhD degree in the field of Computer Science or related technical field, with emphasis in machine learning and statistics.
• 2+ years experience manipulating and analyzing complex, high-dimensionality large scale data using programming languages such as Python, R, or C++.
• Experience communicating complex quantitative analysis in a clear, precise, and actionable manner.
• Experience working with large data sets, experience working with distributed computing tools a plus (Map/Reduce, Hadoop, Hive, etc.).
• Interpersonal experience: cross-group and cross-culture collaboration
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.

Preferred Qualifications:

• Experience in one of the following categories, Reinforcement Learning (Exp. Experience building reinforcement learning models using frameworks, such as PyTorch, TensorFlow or Expertise in policy gradient methods (e.g., actor-critic method) or related methods.) or Automated Machine Learning (Exp. Experience with implementing and applying common AutoML algorithms and techniques such as Bayesian Optimization and Experience with implementing and applying meta-learning and neural architecture search to solve real-world problems.)
• 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 NeurIPS, KDD, WWW, WSDM, AAAI.
• Intent to return to degree-program after the completion of the internship/co-op

Facebook is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law.Facebook is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@fb.com.

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