Applied Research Scientist

Apply quantitative and computational expertise using machine learning, statistics and operations research to bring in step-level improvements in efficiency and scalability across the entire suite of enterprise products.

Work independently and collaboratively with other scientists, engineers, designers, UX researchers, and product managers to accomplish complex tasks that deliver demonstrable value, to Meta�??s Enterprise Products.

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

Initiate and drive applied research projects to completion with statistics methods such as forecasting, time series, hypothesis testing, classification, clustering or regression analysis.

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 Meta's unparalleled data infrastructure.

Design and conduct experiments to solve analytical problems and build models using quantitative, statistical or machine learning approaches.

Apply theoretical expertise and innovation to create or apply new technology, such as identifying new opportunities that will grow the enterprise product�??s long-term roadmap and bring productivity gains for the enterprise.

Use machine learning, natural language understanding, computer vision, statistics and/or mathematical programming tools and techniques to perform data extraction, clean analysis and presentation for medium to large datasets.

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

Ability to evaluate trade-offs between different machine learning solutions.

Ability to conduct A/B test to compare online performance of already shipped models and newly trained models to make launch recommendations.

Experience with Python.