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 Description

RESEARCH 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

/ 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!



learn more about our benefits please visit 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