Staff Data Scientist: Pricing & Revenue ML

CSC Generation; Toronto; Sur place; CAD 100 000 - 130 000; Plein temps

Résumé du poste

A leading technology company in Toronto is seeking a Staff Data Scientist to build and ship production pricing systems. The ideal candidate will have over 7 years of experience in applied ML and proven expertise in pricing strategies. Responsibilities include designing ML systems, collaborating with cross-functional teams, and debugging models to ensure effectiveness. Successful candidates will have strong Python and SQL skills, and a deep understanding of causal inference. This position offers a pivotal role in a rapidly evolving field, with significant business impact.

Qualifications

• 7+ years of experience with production systems that have measurable impact.
• Experience in e-commerce, retail, or pricing-intensive industries.
• Ability to handle messy, real-world data.

Responsabilités

• Design and build ML systems for pricing and demand forecasting.
• Frame ambiguous problems as clear ML tasks.
• Set standards for model evaluation and monitoring.
• Build predictive models across various methods.
• Identify and prevent data leakage and overfitting.
• Design and analyze experiments for pricing decisions.
• Debug models that fail in production.

Connaissances

Applied ML / data science experience

Deep pricing experience

Expert-level Python

Expert-level SQL

Causal inference

Experimental design

Cloud ML platforms familiarity

Formation

MS or PhD in Statistics, Computer Science, Operations Research or related field

Description du poste

A leading technology company in Toronto is seeking a Staff Data Scientist to build and ship production pricing systems. The ideal candidate will have over 7 years of experience in applied ML and proven expertise in pricing strategies. Responsibilities include designing ML systems, collaborating with cross-functional teams, and debugging models to ensure effectiveness. Successful candidates will have strong Python and SQL skills, and a deep understanding of causal inference. This position offers a pivotal role in a rapidly evolving field, with significant business impact.