Careers at Facebook
Software EngineeringData Scientist, Statistics & Decision Science
Menlo Park, CAFacebook was built to help people connect and share, and over the last decade our tools have played a critical part in changing how people around the world communicate with one another. With over a billion people using the service and more than fifty offices around the globe, a career at Facebook offers countless ways to make an impact in a fast growing organization.
Facebook is seeking a Data Scientist to join the Statistics and Decision Science group in our Core Data Science team. The Statistics and Decision Science group's mission is to develop and disseminate innovative inference, modeling, and visualization tools to promote data-driven decision making across the company. The ideal candidate will thrive at this intersection of software engineering and methodology research, possessing a passion for elegant, high performance, and scalable implementations of statistical/visual techniques that provide reliable insights in high impact applications spanning Facebook's internal and external products.
Responsibilities
- Build inferential/visual systems that leverage and integrate with Facebook's various data infrastructures.
- Work closely with other operational and engineering teams to encourage statistical best practices with respect to experimental design and data analysis.
- Develop and demonstrate improved analysis methodologies and educate stakeholders throughout the company.
- Act independently to identify opportunities for improved analysis or improved efficiency through better general purpose statistical tools.
Requirements
- Ph.D. in a relevant technical field, or 4+ years experience in a relevant role
- Comfort manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources
- Ability to communicate complex quantitative analysis and analytic approaches in a clear, precise, and actionable manner
- Fluency with scripting languages such as Python, Ruby, or PHP
- Familiarity with relational databases and SQL-like query languages
- Expert knowledge of a scientific computing language such as R, Python, or Julia
- Experience working with data-distributed query tools a plus (Hadoop, Hive, Presto, etc.)
- One or more of the following:
- -Experience designing batch inference algorithms for data distributed statistical computing platforms such as spark/shark [and/or]
- -Experience designing distributed, asynchronous streaming inference algorithms.
- -Experience with large-scale, performant topic modeling, factor modeling, or matrix factorization.
- -Experience with performant spatio-temporal smoothing and geospatial visualization.
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