Sr Data Scientist

  • Company: LinkedIn
  • Posted: March 26, 2017
  • Reference ID: 1892074388
LinkedIn was built to help professionals achieve more in their careers, and every day millions of people use our products to make connections, discover opportunities, and gain insights. Our global reach means we get to make a direct impact on the world's workforce in ways no other company can. We're much more than a digital resume - we transform lives through innovative products and technology.
Searching for your dream job? At LinkedIn, we strive to help our employees find passion and purpose. Join us in changing the way the world works.
LinkedIn's amazingly rich data about our worldwide network of professionals is a fantastic playground for an applied research engineer. You'll have the opportunity to work with some of the best data people anywhere in an environment which truly values (read: is obsessed with) data-driven decisions.
The Experimentation Team at LinkedIn owns XLNT, a world-class, large-scale end-to-end A/B testing platform that solves not only the day-to-day A/B testing needs across the company, but also sophisticated use cases that are prevalent in a social network setting.
Data scientists of our team contribute to every step of developing a world-class, large-scale A/B testing platform, include:
Develop and improve our A/B testing methodologies and research on the next generation features for the platform Closely collaborate with other team members, including Product Managers, engineers, UI designers and web developers, to ensure the features we build have solid statistical foundation.
Act as an A/B testing expert both in and out of the team.
Provide guidance & advice to external teams when it comes to designing & analyzing experiments.
Have a good understanding of our experimentation infrastructure to be able to diagnose data problems.
Play a critical role in building a strong experimentation ecosystem at LinkedIn.
Actively participate in and contribute to our effort in education and evangelization.
Basic qualifications:
MS/PhD in Statistics or related quantitative field.
Experience with casual inference, statistical hypothesis testing and statistical models.
Experience in R or other statistical software packages.
Experience in Python or other scripting languages.
Preferred Qualifications:
2+ years experience working with large amounts of real data.
Experience working with large scale A/B testing platform in industry Experience with designing and analyzing online A/B tests Experience in Hadoop or other MapReduce paradigms and associated languages such as Pig, Hive, etc.
Experience in Java or C++ or other object-oriented languages.

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