Core Data Science, PhD University Grad

(London, United Kingdom)

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.

Facebook's Core Data Science ( organization works across all products in the company, helping them magnify their success through the use of advanced scientific methods. We are looking for quantitative scientists with a passion for research in statistical inference, algorithms, modeling, machine learning, exploratory data analysis, and social network analysis. You will enjoy getting unique access to several of the richest data sets in the world, cutting edge technology and the ability to see your insights turned into real products on a regular basis.

You will research, guide and implement our statistical methodology, invent measures to understand the data and build systems that extract insights from it. You will work with many teams across all departments in the company to build the tools that inform Facebook's strategy or materially impact over a billion people interacting with each other using our products.

The ideal candidate will have a strong background in computational social science, statistics, math, computer science or a related technical field, will have experience working with statistical modeling, and will have experience building software. They are focused on results, fast learning, and have demonstrated success in using analytics to drive the understanding of a product and an entire market.


  • Apply your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how to effectively direct products to better serve their users
  • Develop and implement our statistical methodology, building models for bias correction, uncertainty estimation, outlier detection, prediction and inference across multiple metrics and dimensions
  • Partner with product and analyst teams to develop methodologies, tools and systems that will increase their success
  • Inform, influence, support, and execute research projects used throughout Facebook to drive product decisions
  • Invent and build software systems that utilize state-of-the-art algorithms from AI and ML to solve the hardest problems facing our products.

Minimum Qualifications

  • Experience with quantitative research and development, preferably about people using products on web or mobile apps, as part of a research lab or with published papers
  • Currently has, or in the process of obtaining a PhD in Math, Statistics, Computer Science, Operations Research, Computational Social Science or other technical field
  • Experience with data analysis using tools such as R or Python and good control of SQL
  • Experience in applying at least one of the following in your research: Survey methodology, quantitative research methods or statistical analysis, modeling, machine learning and other data science techniques
  • Experience with large data sets and distributed computing (Hive/Hadoop) a plus
  • Ability to initiate and drive research projects to completion with minimal guidance
  • The ability to communicate the results of analyses in a clear and effective manner

Preferred Qualifications

  • Competitive Salary including the following benefits apply:
  • Medical Benefits
  • Dental Benefits
  • Vision Benefits
  • Pension Benefits
  • Life Assurance
  • Childcare Benefits
  • Gym Benefits
  • Transport benefits
  • Laundry Benefit
  • Posted: May 30th 2017 Closing date: June 30th 2017

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