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The Role:
- Build systems for causal estimation, uncertainty quantification, and sequential decision-making.
- Answer questions about intervention effects, uncertainty, exploration vs. exploitation, and constrained optimization.
What You’ll Work On:
- Causal and heterogeneous treatment-effect modeling.
- Contextual bandits, active learning, and off-policy evaluation.
- Production ML infrastructure, monitoring, and automated deployment.
What We’re Looking For:
- Exceptional technical ability in machine learning and statistical modeling.
- Experience with causal inference, experimentation, or decision systems.
- Proficiency in Python, SQL, and working with large behavioral datasets.
CSC Generation
CSC Generation builds closed-loop decision systems that use machine learning to operate consumer businesses more intelligently. The company focuses on areas such as pricing, inventory, purchasing, promotions, marketing, and assortment.