MINIMUM QUALIFICATIONS

• Bachelor’s degree (or foreign degree equivalent) in Computer Science, Computer Engineering, Data Science or related field
• Requires completion of an undergraduate-level course, research project, or internship involving the following:
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• Solving analytical problems using quantitative approaches including statistical analysis, hypothesis testing, supervised and unsupervised modeling

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• Manipulating and analyzing data from varying sources using programming languages such as Python, data manipulation tools like Pandas and NumPy, database querying languages such as SQL, and visualization tools such as Matplotlib

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• Communicating quantitative analysis including presentation of complex statistical concepts and results, writing of clear and actionable reports and dashboards, and visualization of data insights

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• Leveraging probabilistic concepts such as statistical distributions, hypothesis testing, expectations, and estimators

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• Familiarity with efficient data structures such as arrays, lists, trees, graphs, and maps

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• Experience leveraging advanced ML techniques such as Bayesian modeling, reinforcement learning, bandits, and causal inference

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• Applying methods for sequential decision-making under uncertainty, including Markov Decision Processes (MDPs) and Reinforcement Learning (RL)

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• Optimizing the architecture and training parameters of Neural Network (NN) models
  
  For those who live in or expect to work from California if hired for this position.

• Work closely with a Product Engineering team to identify and answer important product questions using scientific techniques and research methods.
• Develop novel quantitative methods on top of Meta’s unparalleled data infrastructure.
• Answer product questions and generate insights by using appropriate machine learning, statistical techniques or other relevant scientific modeling approaches on available data.
• Draft software from scratch to implement novel methods.
• Build cross-functional partnerships throughout Meta.
• Communicate best practices in quantitative analysis to partners.
• Work both independently and collaboratively with other Scientists, Engineers, Designers, UX Researchers, and Product Managers to accomplish complex tasks that deliver demonstrable value to Meta’s community of users.
• Drive the collection of new data and the refinement of existing data sources.
• Identify new opportunities within Meta’s long-term roadmap for scientific contributions.