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Overnight Machine Learning Quant Jobs in Toronto, ON

Conduct in-depth exploratory data analysis and apply statistical methods, machine learning ... a related quantitative discipline - or a PhD in a relevant field. * 3+ years of experience ...

... Machine Learning, Computer Vision, or Robotics conferences. - Strong quantitative background and coursework in or working knowledge of linear algebra, calculus, and probability. - Proficient in ...

Conduct in-depth exploratory data analysis and apply statistical methods, machine learning ... a related quantitative discipline - or a PhD in a relevant field. * 3+ years of experience ...

... quantitative field. * 5+ years of data science experience. * In-depth knowledge in machine learning and deep learning models, such as but not limited to, XGboosting, LSTM and LLM etc. * Data ...

D. in a quantitative field such as computer science, applied mathematics, statistics or machine learning - or an equivalent combination of education and experience. You're likely to be a MSFT ...

Implement reusable pipelines and MLOps solutions, to optimize machine learning models and other quantitative algorithms life cycle management. * E2E technical competency including conducting data ...

Solid knowledge of applied Machine Learning, Deep Learning, Large Language Models * Solid cloud ... A graduate or undergraduate degree in a quantitative or analytics-focused discipline (e.g ...

Showing results 41-60

Overnight Machine Learning Quant information

What is the difference between Overnight Machine Learning Quant vs Quantitative Researcher?

AspectOvernight Machine Learning QuantQuantitative Researcher
CredentialsAdvanced degrees in CS, Math, or Stats; programming skillsSimilar; advanced degrees often required
Work EnvironmentFinancial firms, hedge funds, trading desks; fast-paced, data-drivenFinancial institutions, research labs; analytical, research-focused
Industry UsageHigh-frequency trading, algorithmic strategiesMarket analysis, model development
Work HoursOvernight shifts aligned with trading hoursStandard business hours, flexible in some cases

While both roles involve quantitative analysis and programming, Overnight Machine Learning Quants focus on developing models for overnight trading strategies, often working overnight shifts. Quantitative Researchers typically conduct broader market research and model development during regular hours. The roles overlap in skills but differ mainly in work hours and specific application areas.

Infographic showing various Overnight Machine Learning Quant job openings in Toronto, ON as of August 2026, with employment types broken down into 88% Full Time, 6% Part Time, and 6% Contract. Highlights an 63% In-person, 31% Hybrid, and 6% Remote job distribution.

Principal Data Scientist (m/f/d)

AutoTrader.ca

Toronto, ON

Full-time

Retirement

Re-posted 17 days ago


Job description

We are 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. 

AutoTrader.ca is Canada's largest automotive marketplace, with over 25 million monthly visits. 

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

Join our global Data Science team and take a leadership role in shaping the future of the automotive marketplace through cutting-edge AI and machine learning. As a Principal Data Scientist, you'll spearhead high-impact AI initiatives that influence millions of users worldwide, with a focus on both strategic vision and hands-on innovation. 
 
In this role, you'll collaborate cross-functionally with product, engineering, and business teams to design, build, and scale AI solutions that set us apart in the industry. You'll bring deep technical expertise, a passion for innovation, and a strong product mindset to develop ML products that solve real-world problems and deliver measurable business value. 
 
Our ideal candidate is an experienced data science leader who thrives in a dynamic, fast-paced environment that combines the stability of an industry leader with the agility of a startup culture. You are curious, proactive, and committed to continuous learning, especially in emerging areas like Generative AI and Large Language Models (LLMs). 
 
You should be comfortable engaging with all levels of the organization, from peers to executives, and possess the ability to distill complex information into clear, actionable strategies that drive business decisions and create value. 
 
 
What You'll Do:
 
  • Shape the strategic direction and vision of Data Science across the organization by identifying transformative AI/ML opportunities and championing the team's evolving role in a rapidly advancing GenAI landscape.
  • Lead the design and deployment of predictive and generative AI models that power personalization, pricing, search, and optimization in marketplace and fintech domains.
  • Collaborate with product leaders to align ML initiatives with strategic business goals and drive product innovation through data-driven experimentation and modeling.
  • Architect scalable ML infrastructure and automated workflows using cloud-native tools (e.g., AWS, EC2, Kubernetes) to support efficient model training, deployment, and analytics across diverse datasets.
  • Ensure long-term performance and compliance of production AI models though robust governance and monitoring.
  • Provide technical leadership and mentorship to data scientists, shaping an innovative team culture and fostering high-performance and continuous learning.
  • Serve as a cross-functional technical leader, shaping company-wide technical initiatives beyond data science. Partner with engineering, product, and platform teams to influence architecture, innovation agendas, and technical standards across the organization.
  • Act as a senior technical advisor, leading resolution of complex modeling issues and acting as the escalation point for critical incidents.
  • Lead the exploration and strategic application of GenAI, identifying high-impact use cases and guiding their integration across products and platforms. 
 
What You'll Need:
 
  • Advanced academic credentials in a quantitative field such as Computer Science, Engineering, Mathematics, or related discipline
  • 10+ years of experience in data science, machine learning, or applied AI, with a strong portfolio of high-impact projects in production
  • Expert-level programming skills in Python and SQL, and fluency with leading ML/AI frameworks (e.g., scikit-learn, TensorFlow, PyTorch)
  • Direct experience with GenAI/LLM technologies, including tools like Hugging Face, LangChain, OpenAI APIs, vector databases, and fine-tuning methods
  • Deep knowledge of machine learning algorithms (supervised, unsupervised, deep learning), including model evaluation, explainability, and selection for business-critical use cases
  • Strong hands-on experience with cloud infrastructure (AWS), containerization (Docker), and orchestration (Jenkins, Airflow)
  • Proven capability in MLOps, including CI/CD pipelines, model monitoring, versioning, and automated retraining
  • Experience deploying and serving models through APIs (e.g., Flask, FastAPI) in both real-time and batch-processing environments
  • Excellent communication and stakeholder management skills, able to translate complex concepts into actionable insights for non-technical audiences
  • Demonstrated success mentoring teams, guiding technical strategy, and advocating for best practices in experimentation, reproducibility, and ethical AI
  • Experience working in agile product development environments (Scrum/Kanban); experience influencing product roadmaps is a strong plus 
 
Bonus Points 
 
  • Experience in e-commerce, marketplaces, or high-scale consumer platforms
  • Familiarity with automotive data and applications in pricing, inventory optimization, or recommendation systems
  • Contributions to open-source AI/ML projects, publications, or presentations at industry conferences 
 
Experience leveraging AI, Generative AI (GenAI) to enhance engineering productivity, automate repetitive tasks, and optimize workflows. Candidates should demonstrate the ability to integrate AI-driven solutions into their daily work - such as code generation, debugging, reviews, documentation, and decision support-to improve efficiency for themselves and their teams. A proactive approach to exploring and implementing AI tools that drive innovation and streamline development processes is highly valued
 
If this opportunity excites you, but you're unsure whether your background checks every box, we value passion, curiosity, and a growth mindset. Reach out and tell us what strengths you would bring to the team. We look forward to hearing from you! 

The base salary range for this position is CAD 180K - CAD 220K.

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.

What's in it for you:

We understand that there is life at work and life outside of work. Here are a few benefits we all benefit from 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 

For a career where you can drive our business and shape your future, apply now.Â