Staff Data Scientist– Pricing Science

CSC Generation; Toronto; On-site; CAD 100,000 - 130,000; Full time

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

CSC Generation operates $1B+ in revenue across 13 retail brands including Sur La Table, Backcountry, One Kings Lane and more. Pricing is central to how we compete, and we're building the kind of ML-driven pricing capability that the best e-commerce companies in the world have invested in for years.

We're looking for a Staff Data Scientist who's an expert in building and shipping production pricing systems — demand forecasting, price elasticity modeling, dynamic pricing, and the experimentation infrastructure that tells you whether any of it is actually working.

It's a hard problem with real data, real stakes, and real business impact. If you've spent time thinking carefully about how to measure price sensitivity at scale, how to run pricing experiments without destroying margin, or how to build forecasting systems that hold up in production — this is your role.

What You’ll Own

• Design and build production ML systems for pricing, demand forecasting, and related revenue problems
• Frame ambiguous business problems as well-defined ML tasks with clear success criteria and measurable outcomes
• Set the standard for model evaluation, validation, and monitoring — including knowing when CV metrics are misleading and when holdout testing is the only honest answer
• Build robust predictive models across classification, regression, time series, and causal inference
• Identify and prevent data leakage, overfitting, and other failure modes before they reach production
• Design and analyze experiments to measure causal impact of pricing decisions
• Debug models that fail in production — understand why they fail, not just that they do
• Translate model limitations, uncertainty, and risk clearly to both technical and non-technical stakeholders
• Partner with product, engineering, and business teams to ensure ML solutions solve real problems

What You Bring / Requirements

• 7+ years of applied ML / data science experience with a track record of production systems that delivered measurable business impact.
• Deep pricing, demand forecasting, or revenue optimization experience. You've built these models, not just used them.
• Expert-level Python and SQL.
• Strong grounding in causal inference and experimental design. You know the difference between a correlation and a result.
• Ability to work with messy, real-world data and make pragmatic tradeoffs.
• Familiarity with cloud ML platforms (GCP/Vertex AI or AWS/SageMaker).
• MS or PhD in Statistics, Computer Science, Operations Research, or a related quantitative field.
• Self-directed and autonomous. You don't need the problem handed to you fully formed.
• Experience in e-commerce, retail, marketplace, or pricing-intensive industries (airlines, ride-sharing, fintech).

Who We're Not Looking For

• Someone who only knows how to call .fit() and .predict() without understanding the underlying mechanics.
• Someone who builds black-box models they can't explain, debug, or justify.
• Someone who needs detailed instructions or hand-holding for ambiguous problems.
• Someone who over-engineers solutions when a simple approach would suffice.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

For US-based candidates, this posting is intended for candidates that reside in the following states: AZ, DE, FL, GA, IN, LA, MI, MS, MO, NV, NC, OK, PA, TN, TX, UT, WV, WI, and WY.

For Ontario applicants, please note that this posting is for an existing vacancy.

The CSC Generation family of brands provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, provincial, state or local laws. It is unlawful in Massachusetts to require or administer a lie-detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. The CSC Generation family of brands is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need assistance or accommodation due to a disability, please contact [email protected].