Data Scientist

Do you want to work for a world-renowned research institute that pushes the boundaries of biomedical science and health research? Right here in Montreal! At the Research Institute of the McGill University Health Centre (RI-MUHC), you can be part of an organization focused on scientific discovery and innovation in patient-centered medicine. Join us today and make a difference! Job DescriptionRESEARCH INSTITUTE OF THE MUHC The Research Institute of the McGill University Health Centre (RI-MUHC) is a world-renowned biomedical and hospital research centre. Located in Montreal, Quebec, the Institute is the research arm of the McGill University Health Centre (MUHC) affiliated with the Faculty of Medicine at McGill University. The RI-MUHC is supported in part by the Fonds de recherche du Québec - Santé (FRQS). Position Summary Department/Research Program: Health Informatics & Analytics Unit and the Personalized Transplant Care Research Program Under the direct supervision of the Scientific Directors of the Health Informatics & Analytics Unit and the Personalized Transplant Care Research Program, the Data Scientist will play a vital role in building and sustaining the data backbone for a Learning Health System at the MUHC and RI-MUHC. The incumbent will contribute to establishing and maintaining a modern data science environment that supports both clinical care and research innovation. This includes structuring and curating high-quality healthcare data sources, developing advanced statistical and machine learning models, and deploying predictive algorithms to improve research and patient outcomes. A key focus of this role is the development of AI-driven solutions for kidney disease research and transplant outcomes. The successful candidate will design and implement predictive models using clinical, laboratory, and longitudinal healthcare datasets, while incorporating privacy-preserving approaches such as federated learning to enable secure multi-institutional collaboration. The overarching goal is to ensure the ongoing operation of a modern clinical and research analytics ecosystem that supports:

• Integrated clinical and research data analytics
• AI-enabled care workflows
• Dashboard-based performance tracking and quality assessment
• Secure, scalable, multi-site machine learning collaboration

Working closely with clinicians, researchers, data engineers, and institutional partners, the successful candidate will translate complex healthcare challenges into robust, reproducible, and privacy-conscious AI solutions that directly impact patient care and research excellence. General Duties Machine Learning Development & Deployment

• Develop, train, validate, and deploy machine learning models using clinical, laboratory, and longitudinal healthcare datasets.
• Build and maintain end-to-end ML workflows including data preprocessing, feature engineering, model training, validation, deployment, and monitoring.
• Implement model performance tracking, validation frameworks, bias assessment, and quality control checks.
• Train, validate, and evaluate internally developed or vendor-provided ML algorithms using hospital data.

Federated Learning & Privacy-Preserving AI

• Design and implement federated learning pipelines to enable secure multi-site model training.
• Develop decentralized training workflows across multiple institutions or datasets.
• Apply privacy-preserving techniques such as secure aggregation, differential privacy, and compliant model-sharing protocols.
• Deploy and monitor federated learning experiments in secure, regulated environments.

Healthcare Data Engineering & Governance

• Structure, clean, and curate core healthcare datasets.
• Establish quality assurance and data validation monitoring processes.
• Perform de-identification and entity extraction from free-text clinical data.
• Map institutional data to common data models (e.g., OMOP).
• Ensure compliance with healthcare data governance, privacy regulations, and secure ML best practices.

Clinical Collaboration & AI-Enabled Care Workflows

• Collaborate with clinicians, researchers, and interdisciplinary teams to translate clinical questions into ML solutions.
• Build, deploy, and maintain AI-enabled care workflows in partnership with institutional stakeholders.
• Integrate model outputs into analytics dashboards (e.g., Power BI) and reporting pipelines.

Technical Infrastructure & Scholarship

• Inform the acquisition and configuration of tools, platforms, and infrastructure used to manage the ML lifecycle.
• Maintain reproducible workflows using version control and structured documentation.
• Contribute to technical documentation, research publications, grant applications, and scientific presentations.

Website of the organization https://rimuhc.ca/en Education / Experience Education: Doctorate Degree Field of study: Machine Learning, Data Science, Statistics, Computer Science, Bioinformatics, Informatics or a related quantitative field (or equivalent experience) Work experience: PhD: Relevant applied experience preferred. MSc: Minimum 4+ years of experience working on applied data science or machine learning problems. Required Skills

• Knowledge of French is required.
• An advanced knowledge of oral and written English is required, as the position requires regular and complex contact with researchers or international students who are exclusively proficient in English. The position also requires complex writing or in-depth analysis of documents in English related to a research project.
• Experience working in healthcare settings and/or with clinical research teams.
• Experience collaborating with clinicians and interdisciplinary researchers to develop and implement data-driven approaches for clinical care.

Technical & Programming Skills

• Strong programming skills in Python, with experience using ML libraries such as scikit-learn, XGBoost, PyTorch, and TensorFlow.
• Proficiency in SQL, R, and Python for processing and analyzing large-scale datasets in distributed cloud environments.
• Experience working with tabular clinical or healthcare datasets, including familiarity with healthcare data standards (e.g., HL7).
• Experience working in cloud environments and distributed computing infrastructures.
• Familiarity with Git and reproducible machine learning workflows.

Machine Learning & Statistical Expertise

• Graduate-level understanding of machine learning, artificial intelligence, knowledge representation, and strong foundations in statistics.
• Experience developing, evaluating, validating, and deploying machine learning models.
• Experience with survival analysis and time-to-event modeling.
• Strong understanding of model evaluation metrics (e.g., ROC-AUC, calibration metrics, survival model performance measures).
• Understanding of software development principles and ML system design.

Federated Learning & Privacy (Required / Strongly Preferred)

• Hands-on experience with federated learning frameworks such as Flower, TensorFlow Federated, or PySyft.
• Experience designing decentralized training workflows across multiple institutions or datasets.
• Knowledge of privacy-preserving techniques, including secure aggregation, differential privacy, and model-sharing protocols.
• Ability to deploy, manage, and monitor federated learning experiments in secure environments.
• Strong understanding of data privacy, governance, and secure ML practices.

Other Skills

• Excellent verbal and written communication skills.
• Strong interpersonal skills with the ability to work across multidisciplinary teams.
• Demonstrated creativity and problem-solving ability.
• Ability to prioritize and manage multiple competing tasks effectively.

Additional information Status: Temporary, full time (35-hour workweek) Pay Scale: Commensurate with education and experience Work Shift: Monday to Friday 8:30am to 4:30pm Work Site: Glen Site, 1001 Decarie Blvd. This position offers the possibility of a hybrid work arrangement (on-site and remote). ***If you wish to include a cover letter, please attach it with your resume in one document. *** Why work with us?

• 4-week vacation, 5th week after 5 years,
• Bank of 12 paid days (personal days and days for sickness or family obligations),
• 13 paid statutory holidays,
• Modular group insurance plan (including gender affirmation coverage),
• Telemedicine,
• RREGOP (defined benefit government pension plan),
• Training and professional development opportunities,
• Child Care Centres,
• Corporate Discounts (OPUS + Perkopolis),
• Competitive monthly parking rate,
• Employee Assistance Program,
• Recognition Program,
• Flex work options and much more!

https://rimuhc.ca/careers To learn more about our benefits, please visit http://rimuhc.ca/en/compensation-and-benefits THIS IS NOT A HOSPITAL POSITION. Equal Opportunity Employment Program The Research Institute of the McGill University Health Centre hires on the basis of merit and is strongly committed to equity, diversity and inclusion within its community. We welcome applications from all qualified candidates who self-identify as members of racialized groups/visible minorities, women, Indigenous persons, persons with disabilities, ethnic minorities, and 2SLGBTQIA+ persons. We also welcome candidates with the skills and knowledge to productively engage with diverse communities. Persons with disabilities who anticipate needing accommodations for any part of the application process may confidentially contact, research.talent@muhc.mcgill.ca