Senior/Lead Data Scientist (Toronto Time Zone)
About the client
Our client is a leading European online car marketplace, connecting car buyers and sellers across the continent. The platform serves over 30 million monthly users and operates across 18 countries, making it one of the largest and most trusted digital marketplaces for vehicles in Europe.
About the role
As a Senior Data Scientist, you will be a key contributor within the client's global Data Science organization, shaping the AI and machine learning systems that sit at the core of marketplace platforms across Europe and Canada. You will design, build, and operate machine learning and GenAI systems that run in production and matter to the business - working on complex, ambiguous problems, exercising strong technical judgment, and taking responsibility for outcomes, not just models.
While this is a hands-on role, you will also influence technical direction, raise the bar for engineering practices, and enable other data scientists and engineers to succeed.
Responsibilities:
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.
Raise the bar for engineering practices across the Data Science organization and influence technical direction beyond your own projects.
Requirements:
5+ years of experience building and owning production ML systems end-to-end in a real-world environment.
Advanced degree in Computer Science, Engineering, Mathematics, or a comparable field.
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.
Excellent verbal and written English skills.