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.
The Infrastructure Quantitative Engineering group uses statistical and machine learning techniques to support the operations and enable the continued growth of Facebook’s infrastructure. We partner with teams supporting all of Facebook’s infrastructure, focusing on long-term strategic initiatives that make Facebook infrastructure more efficient, reliable, and scalable. We are “full-stack” data scientists, helping to establish product requirements, gather data, design experiments, create models, build software tools and communicate findings. We are looking for hands-on experienced data scientists who can collaborate effectively with partner engineering organizations, fellow data scientists and leadership.
As a Research Data Scientist, you will need to develop subject matter expertise, build trust with partners, recognize the biggest opportunities, create and drive strategy, and leverage data science methodologies to solve hard problems. In your work, you may provide guidance and coordinate with other data scientists to help achieve the goals in broad areas of operation.
1. Identify how data science can be applied to improve, optimize, and expand Facebook’s infrastructure across a variety of domains, with emphasis on long-term and strategic initiatives.
2. Work cross-functionally as a strategic partner to define priorities and develop project roadmaps in synergy with partner teams. Build consensus and earn commitment from partners. Drive execution through fast iteration.
3. Ensure coordination of theirs and others’ projects across related workflows, to maximize impact and avoid duplication and overlaps.
4. Employ languages and tools like Python, R, SQL, and others to drive efficient data exploration and modeling.
5. Build pragmatic, scalable, and statistically rigorous solutions to large-scale web, mobile and data infrastructure problems by leveraging or developing statistical and machine learning methodologies.
6. Generalize methodologies for broader application within and outside their domain.
7. Lead and provide technical mentorship to data scientists, to ensure continuous up-leveling of our expertise.
8. Degree in quantitative field (e.g. Computer Science, Engineering, Mathematics, Statistics, Operations Research or other related field)
9. 6+ years of experience doing quantitative analysis including experience with SQL, other programming languages (e.g, Python) or statistical/mathematical software (e.g, R, SAS, MATLAB)
10. 6+ years of experience with statistics methods such as forecasting, time series, hypothesis testing, classification, clustering or regression analysis
11. 4+ years experience developing production software systems such as data pipelines, deployed machine learning models, or dashboards
12. Experience answering big picture questions by framing the question, turning it into an analytical plan, executing and communicating to stakeholders
13. Experience initiating and driving projects to completion with minimal guidance
14. Advanced degree (Master’s or PhD or equivalent experience) in quantitative field
15. 4+ years of experience doing complex quantitative analysis and working with distributed (i.e. Hive, Hadoop or similar databases) or highly complex datasets
16. 4+ years experience communicating complex research in a clear, precise, and actionable manner
17. 2+ years experience leading teams of other data scientists
**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 firstname.lastname@example.org.