Senior Machine Learning Engineer, Causal & Decision Systems
CSC Generation21 days ago
Toronto, CanadaSenior
Responsibilities
- Build causal and heterogeneous treatment-effect models for pricing and other commercial decisions.
- Develop systems for uncertainty estimation, calibration, contextual bandits, active learning, sequential decision-making, and policy learning.
- Implement constrained optimization, 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 deployment, evaluation, and controlled experiments.
- Help create decision systems that learn from interventions and operate safely across a portfolio of consumer businesses.
Requirements
- Experience with machine learning and statistical modeling.
- Experience in several relevant areas, including causal inference, experimentation, recommendation, advertising, pricing, marketplace, credit, or other decision systems.
- Experience with bandits, reinforcement learning, optimization, active learning, uncertainty estimation, counterfactual evaluation, or production ML systems.
- Strong technical ability and judgment, with experience using Python, SQL, and large behavioral datasets.
- Ability to work across modeling, production deployment, experimentation, and economic outcome evaluation.
Benefits
- Hybrid work arrangement in Toronto, Ontario.
- Comprehensive health, dental, and vision coverage.
- RRSP matching.
- Paid time off.
- Access to cross-brand employee discounts across the CSC Generation portfolio.
- Mandatory in-person interview at the Toronto office is part of the interview process.
Categories