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Key responsibilities include:
- Developing innovative approaches that combine state-of-the-art AI/ML with causal inference to estimate individual treatment effects- Designing and implementing validation approaches using experiments, quasi-experimental methods, and simulations
- Leading research initiatives to resolve scientific ambiguities in applying ML methods to causal inference problems
- 2+ years of building models for business application experience
- PhD, or Master's degree and 2+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience using Unix/Linux
- Experience in professional software development
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