Description
CSC Generation is building closed-loop decision systems that use machine learning to operate consumer businesses more intelligently. The company is starting with pricing and expanding into areas such as inventory, purchasing, promotions, marketing, and assortment.
You will help build systems that estimate causal response and quantify uncertainty, choose actions, generate useful information, observe outcomes, update policies, evaluate challengers, and deploy within guardrails.
The ideal candidate will have experience in several of the following areas:
- Machine learning and statistical modeling
- Causal inference and experimentation
- Recommendation, advertising, pricing, marketplace, credit, or other decision systems
- Bandits, reinforcement learning, optimization, or active learning
- Uncertainty estimation
- Counterfactual evaluation
- Production ML systems
- Python, SQL, and large behavioral datasets
The systems you build should produce measurable economic lift in controlled experiments, generalize across businesses, learn from their own interventions, and safely automate an increasing share of real commercial decisions.
The long-term goal is for the system to become better at operating the business because it has operated the business.
Benefits include comprehensive health, dental, and vision coverage, RRSP matching, paid time off, and access to cross-brand employee discounts across the CSC Generation portfolio.