Principal Data Scientist
Jobgether Canada · CA$160K–CA$182K/yr
Internet Marketplace Platforms · 11-50 employees
About the role
Lead the development of advanced AI models for digital pathology and oncology using large-scale clinical datasets. Collaborate with cross-functional teams to translate complex clinical questions into impactful AI solutions and manage project execution.
What they look for
Requirements
Requires a PhD in a quantitative field and 8+ years of experience in data science or machine learning, preferably within a disease-related field. Candidates must possess expert-level Python proficiency and strong statistical analysis capabilities.
Benefits
Full description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal Data Scientist based in Canada.
This is a senior technical leadership opportunity focused on developing advanced AI models for digital pathology and oncology. You will help shape the next generation of diagnostic products by leveraging large-scale, multimodal clinical and pathology datasets. The role combines hands-on machine learning, statistical analysis, research, and technical leadership. You will work closely with data science, bioinformatics, statistical, medical, and external collaborators to translate complex clinical questions into impactful AI solutions. Your work will contribute to evidence generation, scientific publications, and products designed to support better clinical decision-making. This is an environment for an experienced data scientist who enjoys solving complex problems, mentoring others, and turning emerging AI technologies into meaningful healthcare applications.
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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.
\nHow Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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