Principle Data Scientist

Principal Data Scientist – AutoTrader.CaAutoTrader.Ca is Canada’s largest automotive marketplace. We are shaping the future of automotive retail through cutting‑edge AI and machine learning. As a Principal Data Scientist you will spearhead high‑impact AI initiatives that influence millions of users worldwide.
What You’ll Do
Shape the strategic direction of Data Science across the organization by identifying transformative AI/ML opportunities.
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.
Architect scalable ML infrastructure and automated workflows using cloud‑native tools (e.G., AWS, EC2, Kubernetes) to support efficient model training, deployment, and analytics.
Ensure long‑term performance and compliance of production AI models through robust governance and monitoring.
Provide technical leadership and mentorship to data scientists, fostering a high‑performance, continuous learning culture.
Serve as a cross‑functional technical leader, shaping company‑wide technical initiatives beyond data science.
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 (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 production projects.
Expert‑level programming skills in Python and SQL, and fluency with leading ML/AI frameworks (scikit‑learn, TensorFlow, PyTorch).
Direct experience with GenAI/LLM technologies, including Hugging Face, LangChain, OpenAI APIs, vector databases, and fine‑tuning methods.
Deep knowledge of machine learning algorithms (supervised, unsupervised, deep learning) and 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 (Flask, FastAPI) in real‑time and batch‑processing environments.
Excellent communication and stakeholder management skills, translating complex concepts into actionable insights for non‑technical audiences.
Demonstrated success mentoring teams, guiding technical strategy, and advocating best practices in experimentation, reproducibility, and ethical AI.
Experience working in agile product development environments (Scrum/Kanban) and influencing product roadmaps (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.
Benefits From Day 1
Gym discounts
Employee and Family Assistance program
Virtual wellness events
Conferences & training budget
Regular internal training programs
3% pension matching and multiple income protection options
Use of artificial intelligence in hiring: We use AI in our hiring process to screen, assess, and select applicants for this position.
This job posting is for an existing vacancy.
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