Principal Data Scientist

Accountabilities

• Lead the development of digital pathology AI models using whole-slide imaging data to predict clinical outcomes and pathological or morphological features, with a focus on biological explainability.
• Adapt state-of-the-art open-source AI foundation models to internal datasets, research objectives, and collaborator requirements.
• Identify appropriate data sources for model development and lead efforts to obtain high-quality annotations, labels, and datasets for machine learning initiatives.
• Break down complex data science and machine learning challenges into actionable projects, delegate technical work to junior team members, monitor progress, and ensure high-quality deliverables.
• Partner with internal and external stakeholders to understand clinical and business requirements and translate them into appropriate algorithms, research strategies, and product solutions.
• Collaborate closely with bioinformatics, statistics, medical experts, and other technical teams to document projects and develop analyses, visualizations, and research outputs for peer-reviewed publications.
• Lead cross-functional technical collaboration and manage project execution from research questions through completion.
• Work with medical experts and external collaborators to identify high-value research questions and datasets that strengthen evidence for the utility and performance of AI models.
• Provide technical leadership and mentorship while helping establish effective approaches for solving complex data science problems.
• Contribute to research and development initiatives involving real-world clinical data, evidence generation, and the advancement of diagnostic technologies.

Requirements

• PhD in Data Science, Machine Learning, Applied Mathematics, or a closely related quantitative field.
• 8+ years of experience in data science, applied science, machine learning, or an equivalent technical role within a disease-related field, with oncology experience strongly preferred.
• Expert-level proficiency in Python or a comparable programming language for AI/ML development, particularly in computer vision or digital pathology applications, including data preparation and manipulation.
• Strong statistical analysis capabilities, including survival modeling, hypothesis testing, and multivariate regression with interaction effects.
• Experience working with cloud computing environments; AWS experience is preferred.
• Demonstrated ability to analyze complex datasets, identify meaningful insights, and communicate findings clearly through written documentation, visualizations, presentations, and academic publications.
• Ability to explain sophisticated AI and machine learning concepts effectively to both technical specialists and non-technical stakeholders.
• Proven experience providing technical leadership and managing or mentoring employees, including breaking complex initiatives into clearly defined and delegable projects.
• Strong analytical, problem-solving, storytelling, and communication skills, with exceptional attention to detail.
• Ability to collaborate effectively across multidisciplinary teams in a fast-paced, evolving environment.
• Curiosity and enthusiasm for learning new technologies and adapting to changing research and product requirements.
• Experience serving as a technical leader or manager is highly desirable.
• Familiarity with documentation and submissions in regulated diagnostic environments, such as LDT or IVD, is an advantage.
• Experience working with real-world clinical data and evidence generation is preferred.

Benefits

• Canada-based compensation range of $160,000 – $182,000 CAD.
• Competitive total compensation package, with eligibility for additional discretionary bonuses or incentives and restricted stock units.
• Comprehensive benefits designed to support employees and their well-being.
• Remote-friendly work environment for candidates based in Canada.
• Opportunity to work on advanced AI, digital pathology, oncology, and diagnostic technologies with meaningful patient impact.
• Collaborative, multidisciplinary environment involving data science, bioinformatics, statistics, medical experts, and external partners.
• Opportunities for professional growth, technical leadership, mentorship, and continued learning.
• Inclusive workplace that values diverse perspectives, collaboration, curiosity, and innovation.
• Opportunity to contribute to research programs, scientific publications, and the development of next-generation diagnostic products.
• Access to on-site workspace options where applicable.