Lead Data Scientist

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Data Scientist based in Canada.

This role sits at the intersection of advanced machine learning, client consulting, and technical leadership, driving the design and delivery of end-to-end AI and ML solutions across a diverse set of industries. You will lead high-impact client engagements, translating complex business problems into scalable data science solutions that deliver measurable outcomes. The position combines hands-on model development with strategic advisory responsibilities, requiring both deep technical expertise and strong client-facing communication skills. You will guide project teams, mentor data scientists, and help shape best practices for machine learning delivery. The environment is fast-paced and highly varied, with exposure to everything from startups to enterprise-scale organizations. You will work across modern cloud ML platforms and production-grade Python systems to deploy robust solutions. This is a leadership role for someone who thrives in consulting-driven, innovation-focused environments.

• Lead end-to-end client engagements, including problem scoping, solution design, delivery execution, and stakeholder management.
• Design, build, and deploy machine learning solutions across diverse domains, ensuring scalability, reliability, and business impact.
• Manage and mentor small teams of data scientists, providing technical guidance and supporting professional development.
• Act as the primary technical and strategic point of contact for clients, ensuring alignment and clear communication throughout delivery.
• Develop production-grade ML systems using cloud platforms (e.g., SageMaker, Vertex AI, Azure ML) and Python-based infrastructure.
• Evaluate and integrate emerging tools, frameworks, and methodologies to improve solution quality and delivery efficiency.
• Contribute to best practices in ML engineering, experimentation, and lifecycle management across projects.

Requirements:

• 6+ years of hands-on machine learning experience with a proven track record of deploying models into production environments.
• Strong experience in client-facing or consulting roles, with the ability to manage expectations, scope, and delivery risk effectively.
• Deep expertise in at least one ML domain such as predictive analytics, computer vision, or LLM/agent-based systems, with adaptability across others.
• Strong Python and SQL skills, with experience building production-grade code using frameworks such as PyTorch, Scikit-learn, or Hugging Face.
• Experience working across full ML deployment stacks, including cloud services, Docker, and infrastructure-level development.
• Familiarity with ML lifecycle tools such as MLflow, Weights & Biases, or similar platforms.
• Strong communication skills with the ability to explain complex models to both technical and non-technical stakeholders.
• Advanced degree in a quantitative field (or equivalent practical experience through shipped production work).

Benefits:

• Competitive annual salary ranging from $160,000 to $200,000 USD depending on experience and location.
• Comprehensive employer-paid health, dental, vision, and wellness benefits.
• Flexible vacation and sick leave policy supporting work-life balance.
• Company-provided home office equipment to support remote work.
• Collaborative, team-oriented environment with strong mentorship and knowledge-sharing culture.
• Exposure to diverse, high-impact client projects across multiple industries.
• Regular team events and company-sponsored activities.