Staff Data Scientist: Pricing & Revenue ML

CSC Generation

Toronto

On-site

CAD 100,000 - 130,000

Full time

14 days+

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Job summary

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.

Responsibilities

  • 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.

Skills

Applied ML / data science experience
Deep pricing experience
Expert-level Python
Expert-level SQL
Causal inference
Experimental design
Cloud ML platforms familiarity

Education

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

Job description

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.
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