Research Data Scientist, Machine Learning

In this role, your primary responsibility will be to partner with key stakeholders and lead strategic and quantitative analysis to support and enable the continued growth critical to Meta's Data Center organization. As we plan to grow our Data Center footprint, we need to ​leverage data to drive decisions and ​introduce automation, predictability & optimization to allow us to operate ​efficiently and reliably at scale. Our data scientist team identifies business problems and solves them by using various techniques, algorithms, and models in Statistical Modeling, Machine Learning, Operations Research, and Data Mining. You will have the opportunity to work on a broad spectrum of areas such as hardware or Equipment Failure Prediction, Operational Tools Automation, Demand Forecasting, Alert Optimization, Supply Chain Optimization, Inventory & Capacity Planning, Process Design & Optimization, and Financial Modeling.

Research Data Scientist, Machine Learning Responsibilities:

• Architect and build pragmatic, scalable, and statistically rigorous solutions for data center infrastructure problems by leveraging and developing state-of-the-art statistical and machine learning methods on top of Meta's unparalleled data infrastructure.
• Partner with internal stakeholders on projects to identify and articulate opportunities, see beyond the data to identify solutions that will raise the bar for decision making.
• Define, compute and track business metrics to measure business impact from Machine learning models.
• Articulate impact narratives to and drive decision making with stakeholders and leadership.
• Evangelize Machine Learning methods with data center business groups and drive operational efficiencies through ML driven automation and tools.
• Build and maintain data driven machine learning models, experiments, forecasting algorithms, and optimization models.
• Collaborate with cross-functional data and product teams across business applications to access and manipulate data, explain data gathering requirements, make recommendations, display results, and build efficient and scalable analytical solutions.
• Mentor others as needed on best practices for design and implementation of cutting-edge analytical solutions.

Minimum Qualifications:

• MS in a quantitative field such as Computer Science, Quantitative Finance, Math, Statistics, Physics, or a related Engineering degree.
• Experience with machine learning and statistical methods such as forecasting, time series analysis, hypothesis testing, classification, clustering, regression, or other advanced analytics techniques.
• Experience testable and production-level code and shipping code into production.
• Experience using version control tools such as git or mercurial.
• 7+ years experience in building models and developing algorithms for machine learning, statistics, mathematical programming, and simulation in industry and/or academia.
• 7+ years experience in managing and analyzing large-scale structured and unstructured data using R or Python.
• 7+ years experience in SQL in big data environments (i.e. Hadoop) and data modeling.
• Experience with scientific computing and analysis packages such as NumPy, SciPy, Pandas, scikit-learn, dplyr, or ggplot2.
• Experience with machine learning libraries and packages such as PyTorch, Caffe2, TensorFlow, Keras or Theano.
• Experience with data visualization libraries such as Matplotlib, Pyplot, ggplot2.

Preferred Qualifications:

• PhD in Computer Science or Math or Statistics or relevant fields.
• Knowledge of deep learning research.
• Familiarity with object-oriented programming languages (such as C++ or Java) and visualization tools (such as Tableau).
• Experience executing on the full life cycle of projects through project planning, data collection, model prototyping and deployment, with responsibilities encompassing stakeholder management and communication to cross-functional partners.

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.