The Infrastructure Quantitative Engineering group uses statistical and machine learning techniques to support the operations and enable the continued growth of Meta's infrastructure. We partner with teams supporting all of Meta's infrastructure, focusing on long-term strategic initiatives that make Meta infrastructure more efficient, reliable, and scalable. We are "full-stack" data scientists, helping to establish product requirements, gather data, design experiments, create models, build software tools and communicate findings. We are seeking a Visiting Researcher to join us. Individuals in this role are expected to be PhD researchers who have hands-on experience and can collaborate effectively with partner engineering organizations, fellow data scientists and leadership. The term length would be at least 6 months and the ideal candidate should already have a deep background in statistical and machine learning techniques. As a Research Data Scientist, you will need to develop subject matter expertise, build trust with partners, recognize the biggest opportunities, create and drive strategy, and leverage data science methodologies to solve hard problems. In your work, you may provide guidance and coordinate with other data scientists to help achieve the goals in broad areas of operation.
Visiting Researcher, Research Data Scientist Responsibilities:
- Identify how data science can be applied to improve, optimize, and expand Facebook's infrastructure across a variety of domains, with emphasis on long-term and strategic initiatives.
- Work cross-functionally as a strategic partner to define priorities and develop project roadmaps in synergy with partner teams. Build consensus and earn commitment from partners. Drive execution through fast iteration.
- Ensure coordination of theirs and others' projects across related workflows, to maximize impact and avoid duplication and overlaps.
- Employ languages and tools like Python, R, SQL, and others to drive efficient data exploration and modeling.
- Build pragmatic, scalable, and statistically rigorous solutions to large-scale web, mobile and data infrastructure problems by leveraging or developing statistical and machine learning methodologies.
- Generalize methodologies for broader application within and outside their domain.
- Lead and provide technical mentorship to data scientists, to ensure continuous up-leveling of our expertise.
- Degree in quantitative field (e.g. Computer Science, Engineering, Mathematics, Statistics, Operations Research or other related field)
- Experience initiating and driving projects to completion with minimal guidance
- Experience answering big picture questions by framing the question, turning it into an analytical plan, executing and communicating to stakeholders
- 1+ years of experience doing quantitative analysis including experience with SQL, other programming languages (e.g, Python) or statistical/mathematical software (e.g, R, SAS, MATLAB)
- 1+ years experience developing production software systems such as data pipelines, deployed machine learning models, or dashboards
- 1+ years of experience with statistics methods such as forecasting, time series, hypothesis testing, classification, clustering or regression analysis
- 1+ years of experience doing complex quantitative analysis and working with distributed (i.e. Hive, Hadoop or similar databases) or highly complex datasets
- 1+ years experience communicating complex research in a clear, precise, and actionable manner
- Advanced degree (Master's or PhD or equivalent experience) in quantitative field
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