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Senior Data Scientist - Toronto (m/f/d)

Toronto, ON (Canada)

Pay
CAD 130,000–180,000/year · BaseAnnual period assumed — pay source
Annual bonus structure The base salary range for this position is CAD $130k – $180k. This range reflects the expected compensation at the time of posting. The final offer may vary and can be higher based on relevant skills, experience, location, and market conditions. Based on the role, the total rewards package may also include benefits, bonus, and other employee offerings.
Read the full posting
Work setup
Unconfirmed
Employment
Permanent — employment source
As Senior Data Scientist, you will be key contributor within our global Data Science organization, shaping AI and machine learning systems that sit at the core of our marketplace platforms across Europe and Canada. You design, build, and operate machine learning and GenAI systems that run in production and matter to the business. You work on complex, ambiguous problems, exercise strong technical judgment, and take responsibility for outcomes - not just models. While this is a hands-on role, you are also expected to influence technical direction, raise the bar for engineering practices, and enable other data scientists and engineers to succeed. This position is permanent and based in Toronto. What you’ll do
Read the full posting
Apply at AutoTrader.ca

What you’ll work on

Full posting
  • Own ML and GenAI systems end-to-end in production, including problem framing, system design, deployment, monitoring, and continuous improvement

  • Partner closely with Product, Engineering, and Business leaders to turn ambiguous problems into ML-enabled product solutions with clear outcomes

  • Mentor other data scientists through hands-on technical guidance, design reviews, and shared ownership of systems

From the employer’s posting
What you’ll do Own ML and GenAI systems end-to-end in production, including problem framing, system design, deployment, monitoring, and continuous improvement Make sound architectural and methodological decisions for ML systems on AWS, balancing robustness, observability, cost, and long-term maintainability
Make sound architectural and methodological decisions for ML systems on AWS, balancing robustness, observability, cost, and long-term maintainability Partner closely with Product, Engineering, and Business leaders to turn ambiguous problems into ML-enabled product solutions with clear outcomes Operate and evolve ML systems deployed across multiple countries and markets, accounting for differences in data distributions, regulations, and constraints
Operate and evolve ML systems deployed across multiple countries and markets, accounting for differences in data distributions, regulations, and constraints Mentor other data scientists through hands-on technical guidance, design reviews, and shared ownership of systems What you’ll need

What you’ll bring

All qualifications

Core experience

  • 6+ years of experience building and owning production ML systems end-to-end in a real-world environment
  • Solid experience with AWS and MLOps practices, including deployment, monitoring, and operating ML systems at scale
  • Practical experience applying GenAI / LLMs in applied or production contexts, with a clear understanding of trade-offs and limitations
  • Ability to influence technical decisions through clear judgment and collaboration, not formal authority
  • Experience supporting and guiding more junior data scientists through hands-on collaboration, code reviews, and technical feedback
Qualification wording
6+ years of experience building and owning production ML systems end-to-end in a real-world environment
Solid experience with AWS and MLOps practices, including deployment, monitoring, and operating ML systems at scale
Practical experience applying GenAI / LLMs in applied or production contexts, with a clear understanding of trade-offs and limitations
Ability to influence technical decisions through clear judgment and collaboration, not formal authority
Experience supporting and guiding more junior data scientists through hands-on collaboration, code reviews, and technical feedback

Tools in this posting

  • Python
  • AWS
Source — Tool mentions in context
- 6+ years of experience building and owning production ML systems end-to-end in a real-world environment - Strong hands-on expertise in Python and modern ML frameworks, with the ability to ship, operate, and evolve ML systems in production - Solid experience with AWS and MLOps practices, including deployment, monitoring, and operating ML systems at scale
- Own ML and GenAI systems end-to-end in production, including problem framing, system design, deployment, monitoring, and continuous improvement - Make sound architectural and methodological decisions for ML systems on AWS, balancing robustness, observability, cost, and long-term maintainability - Partner closely with Product, Engineering, and Business leaders to turn ambiguous problems into ML-enabled product solutions with clear outcomes
- Strong hands-on expertise in Python and modern ML frameworks, with the ability to ship, operate, and evolve ML systems in production - Solid experience with AWS and MLOps practices, including deployment, monitoring, and operating ML systems at scale - Practical experience applying GenAI / LLMs in applied or production contexts, with a clear understanding of trade-offs and limitations

Job description

View original posting ↗

We are TRADER, a Canadian leader in digital automotive solutions. Our flagship brands - AutoTrader.ca, AutoSync, Dealertrack Canada and CMS - help Canadians buy, sell, and finance vehicles with confidence. 

Learn more at tradercorporation.com. 

As part of AutoScout24 group, Europe’s largest online car marketplace, we’re shaping the future of automotive retail in Canada and beyond. 

 

As Senior Data Scientist, you will be key contributor within our global Data Science organization, shaping AI and machine learning systems that sit at the core of our marketplace platforms across Europe and Canada. 

You design, build, and operate machine learning and GenAI systems that run in production and matter to the business. You work on complex, ambiguous problems, exercise strong technical judgment, and take responsibility for outcomes - not just models. While this is a hands-on role, you are also expected to influence technical direction, raise the bar for engineering practices, and enable other data scientists and engineers to succeed. This position is permanent and based in Toronto. 

What you’ll do 

  • Own ML and GenAI systems end-to-end in production, including problem framing, system design, deployment, monitoring, and continuous improvement 
  • Make sound architectural and methodological decisions for ML systems on AWS, balancing robustness, observability, cost, and long-term maintainability 
  • Partner closely with Product, Engineering, and Business leaders to turn ambiguous problems into ML-enabled product solutions with clear outcomes 
  • Operate and evolve ML systems deployed across multiple countries and markets, accounting for differences in data distributions, regulations, and constraints 
  • Mentor other data scientists through hands-on technical guidance, design reviews, and shared ownership of systems 

What you’ll need  

  • Advanced degree in Computer Science, Engineering, Mathematics, or a comparable field 
  • 6+ years of experience building and owning production ML systems end-to-end in a real-world environment 
  • Strong hands-on expertise in Python and modern ML frameworks, with the ability to ship, operate, and evolve ML systems in production 
  • Solid experience with AWS and MLOps practices, including deployment, monitoring, and operating ML systems at scale 
  • Practical experience applying GenAI / LLMs in applied or production contexts, with a clear understanding of trade-offs and limitations 
  • Ability to influence technical decisions through clear judgment and collaboration, not formal authority 
  • Experience supporting and guiding more junior data scientists through hands-on collaboration, code reviews, and technical feedback 
  • Strong sense of ownership and accountability for outcomes, with a pragmatic approach to trade-offs and delivery 

What’s in it for you 

We understand that there is life at work and life outside of work. Here are a few benefits that support us to be our creative best.   

  • Gym discounts 
  • Employee and Family Assistance program 
  • Virtual wellness events 
  • Conferences & training budget 
  • Regular internal training programs 
  • Financial planning with 3% matching Pension  
  • Competitive salary 
  • Annual bonus structure 

The base salary range for this position is CAD $130k – $180k.

This range reflects the expected compensation at the time of posting. The final offer may vary and can be higher based on relevant skills, experience, location, and market conditions. Based on the role, the total rewards package may also include benefits, bonus, and other employee offerings. 

Use of Artificial Intelligence in Hiring: We use artificial intelligence (“AI”) in our hiring process, including to screen, assess, or select applicants for this position.

Vacancy Status: This job posting is for an existing vacancy. 

 

Use of Artificial Intelligence in Hiring: We use artificial intelligence (“AI”) in our hiring process, including to screen, assess, or select applicants for this position.

Vacancy Status: This job posting is for an existing vacancy.

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.

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Source & posting history

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Pay
Annual bonus structure The base salary range for this position is CAD $130k – $180k. This range reflects the expected compensation at the time of posting. The final offer may vary and can be higher based on relevant skills, experience, location, and market conditions. Based on the role, the total rewards package may also include benefits, bonus, and other employee offerings.
Location & working pattern

Toronto, ON (Canada)

Working pattern and location restrictions need checking in the full posting.

Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

Status in our records
Active
First seen by us
Mar 7, 2026
Recorded sightings
56
Last seen by us
Oct 8, 2026

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