Senior Machine Learning Engineer, Causal & Decision Systems
CSC Generation21 days ago
Responsibilities
- Build causal and heterogeneous treatment-effect models for pricing and other commercial decisions.
- Develop systems for uncertainty estimation, contextual bandits, active learning, sequential decision-making, policy learning, and constrained optimization.
- Implement counterfactual and off-policy evaluation, experimentation, and champion/challenger systems.
- Build production ML infrastructure with monitoring and automated deployment.
- Own problems end to end from framing and modeling through production deployment and evaluation.
- Deliver measurable economic lift through controlled experiments while respecting inventory, margin, vendor, customer, and operational constraints.
Requirements
- Experience in machine learning and statistical modeling.
- Experience with causal inference and experimentation.
- Experience with recommendation, advertising, pricing, marketplace, credit, or other decision systems.
- Experience with bandits, reinforcement learning, optimization, or active learning.
- Experience with uncertainty estimation and counterfactual evaluation.
- Experience building production ML systems.
- Proficiency with Python and SQL and experience working with large behavioral datasets.
- Exceptional technical ability and judgment, with experience in several of the listed areas.
Benefits
- Comprehensive benefits including paid time off, 401(k) match, medical, dental, vision, and supplemental coverage.
- Employee discounts across portfolio brands.
- Hybrid work arrangement in Austin, Texas.
- Mandatory in-person interview and final on-site visit at the Austin office.
- Candidates for US-based roles must reside in one of the listed eligible states.
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