Facebook Data Scientist, Product 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.


We’re looking for data scientists to work on our core and business products (Instagram, Ads, Messaging, Identity, Growth & Engagement, Mobile, Search, Privacy, Payments ) with a passion for Internet technology to help drive informed business decisions for Facebook. You will enjoy working with one 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. The perfect candidate will have a background in a quantitative or technical field, will have experience working with large data sets, and will have some experience in data-driven decision making. You are scrappy, focused on results, a self-starter, and have demonstrated success in using analytics to drive the understanding, growth, and success of a product. These positions are located in our London office. Competitive Salary including the following benefits apply:

-Medical Benefits

-Dental Benefits

-Vision Benefits

-Pension Benefits

-Life Assurance

-Childcare Benefits

-Gym Benefit

-Transport Benefit

-Laundry Benefit

Posted: 24th August 2017 Closing date: 21st September 2017

Required Skills:

  1. Apply your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how our users interact with our core/business products

  2. Partner with Product and Engineering teams to solve problems and identify trends and opportunities

  3. Inform, influence, support, and execute our product decisions and product launches.

  4. The Data Scientist Analytics role has work across the following four areas:

    • Data Infrastructure
  5. Working in hadoop and hive primarily, sometimes mysql, oracle, and vertica

  6. Authoring pipelines via SQL and python based ETL framework

  7. Building key data sets to empower operational and exploratory analysis

  8. Automating analyses

    • Product Operations
  9. Setting goals

  10. Designing and evaluating experiments monitoring key product metrics, understanding root causes of changes in metrics

  11. Building and analyzing dashboards and reports

    • Exploratory Analysis
  12. Proposing what to build in the next roadmap

  13. Understanding ecosystems, user behaviors, and long-term trends

  14. Identifying levers to help move key metrics

  15. Evaluating and defining metrics

  16. Building models of user behaviors for analysis or to power production systems

    • Product Leadership
  17. Influencing product teams through presentation of work

  18. Communicating of state of business, experiment results, etc to product teams

  19. Spreading best practices to analytics and product teams

Minimum Qualifications:

  1. Experience doing quantitative analysis.

  2. BA/BS in Computer Science, Math, Physics, Engineering, Statistics or other technical field. Advanced degrees preferred.

  3. Fluency in SQL or other programming languages. Some development experience in at least one scripting language (PHP, Python, Perl, etc.)

  4. Ability to initiate and drive projects to completion with minimal guidance

  5. The ability to communicate the results of analyses in a clear and effective manner

  6. Basic understanding of statistical analysis.

  7. Preferred experience with a statistical package such as R, MATLAB, SPSS, SAS, Stata, etc.

  8. Preferred experience with an Internet-based company.

  9. Experience with large data sets and distributed computing (Hive/Hadoop) a plus.

Industry: Internet