Facebook Research Scientist, Applied Statistician in 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 is seeking an Applied Statistician to join our Core Statistics team to help us make the best decisions and build the best products with our data. Individuals in this role are expected to be comfortable working as a software engineer and as an applied statistics researcher. The ideal candidate will have a keen interest in developing and applying advanced statistical methodologies, as well as building tools and visualizations that can help data scientists, engineers, and product managers get the most out of these techniques.
Competitive compensation including the following: Medical Benefits, Dental Benefits, Vision Benefits, Pension Benefits, Life Assurance, Ride2Work, Childcare Benefits, Gym Benefits, Transport benefits, Laundry Benefit
Posted: 13th July 2018 Closing date: 10th August 2018
Work closely with data scientists, engineers, and product managers to identify important and common statistical challenges.
Develop novel approaches where traditional methods do not meet requirements for flexibility, scale, or accuracy.
Engineer and deploy solutions for broad sets of statistics problems at Facebook, such as:
Design and analysis of experiments.
Dimensionality reduction and clustering.
Communicate empirical findings and methodologies to product managers and engineers.
Drive the collection of new data and the refinement of existing data sources.
PhD in Statistics, or a Social Science discipline (e.g. Economics, Sociology, Political Science) with experience in methodological research.
Experience publishing research or open source project which develops novel statistical methodologies, in particular methodologies related to sampling, experimentation, bias reduction, and data visualization.
Experience manipulating and analyzing high-volume, high-dimensionality data from varying sources.
Experience communicating quantitative analysis.
Experience with relational databases and SQL.
Experience using R and/or Python to analyze data and build analysis pipelines.
We welcome applicants coming directly from Academia (PhD or PostDoc) or coming from Industry with experience working as an applied statistician