RESEARCH SCIENTIST, STATISTICS & PRIVACY
- 10,001+ employees · Internet Publishing
- Actively recruiting
About the jobOur Statistics & Privacy team focuses on establishing step-change improvements to advance our long-term business growth. The team's expertise spans many domains including statistics, machine learning, economics, and cryptography. We develop methodologies, design and prototype solutions, and partner across Meta to launch these solutions such that 3 billion people, 200 million businesses, and 10 million advertisers can benefit. Examples include experimentation platforms, ranking and recommender systems, and privacy-enhancing technologies.Meta seeks industry-experienced research scientists to join Statistics & Privacy and serve as scientific leaders for cutting-edge applied research spanning artificial intelligence, machine learning, and statistics. Such work necessitates identification and evaluation of new research opportunities, and development of scientifically rigorous systems. Research scientists drive forward prototypes and methodologies, and build consensus with engineering stakeholders as to the scientific and strategic merit of our initiatives. This role will focus on developing a sequence of creative approaches that form a long-term strategy to power our advertising capabilities. This work is critical to our long-term product development, and we expect research scientists to provide both scientific expertise and creative solutions to accelerate their project area.
Research Scientist, Statistics & Privacy Responsibilities:
- Assess potential opportunities and execute world-class research associated with your area of scientific expertise
- Design and prototype new algorithms, optimization methods, and system architectures to advance our long-term priorities
- Establish approaches to rigorously assess validity and relative performance of new technologies or strategies
- Build cross-functional collaborations with Engineering, Product and Analytics teams to shape roadmaps with a balance of scientific rigor and strategic considerations
- Learn new tools, systems, and programming languages quickly as required by the particular project you are working on
- Apply communication skills to engage diverse audiences on technical topics and nuanced insights
- Develop patent applications, white papers, conference presentations, and publications that are broadly appealing and accessible beyond a core scientific audience.
- PhD in computer science, electrical engineering, statistics, mathematics, or a related field
- Understanding of modern machine learning techniques and their mathematical underpinning
- Expertise in statistics (particularly causal inference and Bayesian inference) or deep learning (particularly ranking, retrieval and recommender systems), including addressing challenges from incomplete, unrepresentative, and mislabeled data
- Proficiency designing and implementing analytical and/or algorithmic solutions, tailored to particular business needs and tested on large data sets
- Proficiency in Python
- Proficiency communicating analysis and establishing confidence among audiences who do not share your disciplinary background or training
- First-author publications at peer-reviewed conferences (e.g. NeurIPS, ICML, ACL, EMNLP, SIGIR, WWW, AISTATS) or disciplinary journals (e.g. JAIR, JMLR, TKDE)
- Development experience specific to online advertising and/or electronic commerce
- Proficiency with Presto, Hive or Spark SQL
- Experience developing and debugging in C/C++ and Java
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