Causal ML Scientist for Pricing & Experiments

Amazon Science; Seattle (WA); In loco; USD 136.000 - 184.000; Tempo pieno

Descrizione del lavoro

Amazon Science is seeking a Research Scientist to own causal inference at the intersection of machine learning and pricing experimentation. You will design, train, and deploy end-to-end causal ML pipelines, including CATE estimation models, and serve as the causal ML methodology expert for the team.

You will partner with senior economists and engineers to productionize causal methods, evaluate new approaches, and contribute to pricing experiments.

Competenze

• PhD, or Master's degree and 4+ years of quantitative field research experience.
• Experience applying scientific principles to business problems and products.
• Experience analyzing both experimental and observational data sets.

Mansioni

• Design, train, evaluate, and deploy end-to-end causal ML pipelines for pricing use cases, including CATE estimation models and heterogeneous treatment effect frameworks.
• Serve as the team's causal ML methodology expert — defining identification strategies, model selection criteria, evaluation standards, and the tradeoffs between econometric and ML approaches to causal estimation.
• Contribute causal analysis methodology to pricing A/B test post-analysis and build reusable tooling that economists and other non-ML scientists can adopt.
• Assess emerging causal inference methods (e.g., synthetic difference-in-differences, generalized random forests, causal representation learning) for applicability to Amazon's pricing context, and author internal methodology proposals for adoption.
• Partner with senior economists on identification strategy and causal assumptions, collaborate with software and data engineering partners on production deployment, and align with product managers on experiment design requirements.

Conoscenze

R

MATLAB

Python

Java

C++

Formazione

PhD or Master’s + 4+ years quantitative field research

Strumenti

Python

Java

C++

Descrizione del lavoro

Amazon Science is seeking a Research Scientist to own causal inference at the intersection of machine learning and pricing experimentation. You will design, train, and deploy end-to-end causal ML pipelines, including CATE estimation models, and serve as the causal ML methodology expert for the team.

You will partner with senior economists and engineers to productionize causal methods, evaluate new approaches, and contribute to pricing experiments.