May 31, 2022, 4 p.m. | Alyssa Hughes

Microsoft Research www.microsoft.com

Identifying causal effects is an integral part of scientific inquiry. It helps us understand everything from educational outcomes to the effects of social policies to risk factors for diseases. Questions of cause-and-effect are also critical for the design and data-driven evaluation of many technological systems we build today.  To help data scientists better understand and […]


The post DoWhy evolves to independent PyWhy model to help causal inference grow appeared first on Microsoft Research.

causal inference dowhy independent inference research blog

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Machine Learning Engineer (m/f/d)

@ StepStone Group | Düsseldorf, Germany

2024 GDIA AI/ML Scientist - Supplemental

@ Ford Motor Company | United States