Facebook Data Scientist, Analytics - Instagram in Menlo Park, California

Intro:

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.

Summary:

As Messenger and Messenger Lite continues to expand to all corners of the world, having performant apps matters more than ever. The vast majority of our users access Messenger using old devices and unreliable networks, and bad performance leads to less engaged users and a poor user experience. In this role you will be working closely with the team responsible for making sure the Messenger app delivers the best possible performance across iOS, Android and Web platforms. Our team works cross-functionally with product and infrastructure teams across Messenger to improve app start time, scrolling performance as well as reduce crashes and minimize resources consumption. We’re looking for a thought leader in this space to help us frame up and prioritize all the performance investments that we’re making across the company. This position will directly engage with the CTO for the Messenger app and have the opportunity to directly shape our investments and roadmap for the next 3 years.Some key challenges we’re looking to solve in the next year include:How often do users have a “bad experience” while using the app? How can we quantify this and how does it affect engagement?What sectors of the population are the most sensitive to performance regressions and how should we adapt our strategy as a result?How should we prioritize our efforts across different users and performance metrics to deliver the best possible performing app?

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 both our consumer and 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:

  5. Product Operations

  6. Forecasting and setting product team goals

  7. Designing and evaluating experiments

  8. Monitoring key product metrics, understanding root causes of changes in metrics

  9. Building and analyzing dashboards and reports

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

  11. Evaluating and defining metrics

  12. Exploratory Analysis

  13. Proposing what to build in the next roadmap

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

  15. Identifying new levers to help move key metrics

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

  17. Product Leadership

  18. Influencing product teams through presentation of data-based recommendations

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

  20. Spreading best practices to analytics and product teams

  21. Data Infrastructure

  22. Working in Hadoop and Hive primarily, sometimes MySQL, Oracle, and Vertica

  23. Automating analyses and authoring pipelines via SQL and python based ETL framework

Minimum Qualifications:

  1. 7+ years experience doing quantitative analysis

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

  3. Experience in SQL or other programming languages

  4. Development experience in any scripting language (PHP, Python, Perl, etc.)

  5. Experience communicating the results of analyses with product and leadership teams to influence the strategy of the product

  6. Knowledge of statistics (e.g., hypothesis testing, regressions)

  7. Experience manipulating data sets through statistical software (ex. R, SAS) or other methods

Preferred Qualifications:

  1. Advanced degrees

  2. Experience with distributed computing (Hive/Hadoop)

Industry: Internet

Equal Opportunity: Facebook is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Facebook is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@fb.com.