Applied Research Scientist (University Grad)

Posted 14 hours ago
Main Location
Menlo Park, CA, United States
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Facebook's Enterprise Engineering team develops and maintains scalable products that power the enterprise. Enterprise Product Applied Research team is composed of applied quantitative and computational experts using machine learning, statistics and operations research to bring in step-level improvements in efficiency and scalability across the entire suite of enterprise products. As a member of Enterprise Engineering, you will play a key role in reimagining productivity by shipping transformative products that serve diverse aspects of the enterprise.

  • Build pragmatic, scalable, and statistically rigorous scientific solutions for large scale enterprise problems by leveraging or developing state-of-the-art machine learning and optimization methodologies on top of Facebook's unparalleled data infrastructure.
  • Work cross-functionally to define problem statements, collect data, build analytical models and deploy them at scale.
  • Build and maintain data driven machine learning models, optimization models, experiments and forecasting algorithms.
  • Apply excellent communication skills in order to develop cross-functional partnerships and spread scientific best practices.
  • Be able to work both independently and collaboratively with other scientists, engineers, designers, UX researchers, and product managers to accomplish complex tasks that deliver demonstrable value to Facebook's Enterprise Products.
  • Think creatively, proactively, and futuristically to identify new opportunities that will grow the enterprise product’s long-term roadmap and bring productivity gains for the enterprise.

MINIMUM QUALIFICATIONS

  • Currently has, or is in the process of obtaining a Masters degree in quantitative field (e.g. computer science, engineering, operations research, electrical engineering, statistics, mathematics and related fields)
  • Experience working with machine learning, natural language understanding, computer vision, statistics or mathematical programming tools and techniques
  • Experience performing data extraction, cleaning, analysis and presentation for medium to large datasets
  • Experience with at least one programming language (i.e. Python, R, Java, or C++)
  • Experience writing SQL queries
  • Experience with scientific computing and analysis packages such as NumPy, SciPy, Pandas, Scikit-learn, dplyr, or ggplot2
  • Experience with machine learning libraries and packages such as PyTorch, Caffe2, TensorFlow, Keras or Theano
  • Experience with statistics methods such as forecasting, time series, hypothesis testing, classification, clustering or regression analysis
  • Experience communicating scientific work in a clear and effective manner
  • Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment

PREFERRED QUALIFICATIONS

  • Currently has, or is in the process of obtaining a Masters degree in quantitative field (e.g. computer science, engineering, operations research, electrical engineering, statistics, mathematics and related fields)
  • Experience working with machine learning, natural language understanding, computer vision, statistics or mathematical programming tools and techniques
  • Experience performing data extraction, cleaning, analysis and presentation for medium to large datasets
  • Experience with at least one programming language (i.e. Python, R, Java, or C++)
  • Experience writing SQL queries
  • Experience with scientific computing and analysis packages such as NumPy, SciPy, Pandas, Scikit-learn, dplyr, or ggplot2
  • Experience with machine learning libraries and packages such as PyTorch, Caffe2, TensorFlow, Keras or Theano
  • Experience with statistics methods such as forecasting, time series, hypothesis testing, classification, clustering or regression analysis
  • Experience communicating scientific work in a clear and effective manner
  • Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment

Facebook's mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, we're building a different kind of company that connects billions of people around the world, gives them ways to share what matters most to them, and helps bring people closer together. Whether we're creating new products or helping a small business expand its reach, people at Facebook are builders at heart. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities - we're just getting started.

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Applied Research Scientist (University Grad)
Facebook, Inc.