QualificationsSQLMentoringAnalyticsRDistributed systemsBachelor’s degree
Own analytics for a major ML/technology/platform area given company priorities.
Lead analytics projects end-to-end in partnership with Product, Engineering, and cross-functional teams to inform, influence, support, and execute research and product strategy and investment decisions.
Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches.
Apply technical expertise with machine learning, quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses.
Partner with cross-functional engineering and product teams to derive quantitative understanding of Meta’s ML infrastructure and ML applications.
Inform direction and strategic decisions for the future of ML and large scale distributed systems at Meta.
Identify opportunities and develop solutions in existing large scale distributed systems and ML stack.
Define, understand, and test opportunities and levers to improve the product through ML models and applications, and drive ML-modeling roadmaps through your insights and recommendations.
Contribute towards advancing the Data Science discipline at Meta, including but not limited to driving data best practices (e.g. analysis, goaling, experimentation, machine learning), improving analytical processes, scaling knowledge and tools, and mentoring other data scientists.
Carry out very complex analyses, often combining multiple projects or approaches, requiring deep expertise in the corresponding ML/technology/platform area.
Currently has, or is in the process of obtaining a Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
Experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R).
Graduate level degree in a quantitative field, e.g. Computer Science, Statistics, Mathematics, Engineering, Physics.
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