Applied Research Scientist, Enterprise Products

Facebook

Menlo Park, CA 94025

Posted 1 month ago

Job Description

**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:**


Facebook's Enterprise Engineering team develops and maintains scalable products that power the enterprise. Enterprise Product Applied Research team is composed of applied quantitative and computational experts using machine learning, statistics and operations research to bring in step-level improvements in efficiency and scalability across the entire suite of enterprise products. As a member of Enterprise Engineering, you will play a key role in reimagining productivity by shipping transformative products that serve diverse aspects of the enterprise.


**Required Skills:**


1. Build pragmatic, scalable, and statistically rigorous scientific solutions for large scale enterprise problems by leveraging or developing state of the art machine learning and optimization methodologies on top of Facebook's unparalleled data infrastructure


2. Work cross-functionally to define problem statements, collect data, build analytical models and deploy them at scale


3. Build and maintain data driven machine learning models, optimization models, experiments and forecasting algorithms


4. Apply excellent communication skills in order to develop cross-functional partnerships and spread scientific best practices


5. Be able to work both independently and collaboratively with other scientists, engineers, designers, UX researchers, and product managers to accomplish complex tasks that deliver demonstrable value to Facebook's Enterprise Products


6. Think creatively, proactively, and futuristically to identify new opportunities that will grow the enterprise product’s long-term roadmap and bring productivity gains for the enterprise


7. Lead and provide technical mentorship to data scientists, to ensure continuous up-leveling of our expertise


8. Generalize methodologies for broader application within and outside their domain


**Minimum Qualifications:**


9. Ph.D. or Masters degree in quantitative field (e.g. computer science, engineering, operations research, electrical engineering, statistics, mathematics and related fields)


10. 6+ years of experience solving analytical problems and building models using quantitative, statistical or machine learning approaches


11. 4+ years experience developing production software systems such as data pipelines, deployed machine learning models, or dashboards


12. Understanding of modern machine learning techniques and their mathematical underpinnings


13. Experience answering big picture questions by framing the question, turning it into an applied research plan, executing and communicating to stakeholders


14. Experience with machine learning, natural language understanding, computer vision, statistics or mathematical programming tools and techniques


15. Experience performing data extraction, cleaning, analysis and presentation for medium to large datasets


16. Experience with at least one programming language (i.e. Python, R, Java, or C++)


17. Experience writing SQL queries


18. Experience with scientific computing and analysis packages such as NumPy, SciPy, Pandas, Scikit-learn, dplyr, or ggplot2


19. Experience with machine learning libraries and packages such as PyTorch, Caffe2, TensorFlow, Keras or Theano


20. Experience with statistics methods such as forecasting, time series, hypothesis testing, classification, clustering or regression analysis


21. Experience initiating and driving applied research projects to completion with minimal guidance


22. Experience communicating scientific work in a clear and effective manner


**Preferred Qualifications:**


23. PhD preferred with track record of publications in top international conferences or scientific journals


24. 4+ years experience communicating complex research in a clear, precise, and actionable manner


25. 2+ years experience leading teams of other data scientists


26. Experience working with distributed computing tools (Hadoop, Hive, Spark, etc.)


27. Experience in object oriented programming such as Python, C++, Java


28. Experience using deep learning, natural language processing or computer vision in a production environment


29. Proficiency in algorithmic complexity


**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.



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