Research Data Analyst Neurotrauma(Job Id 16540) Job title: Research Data Analyst Neurotrauma Site: CA:ON:Toronto:St. Michael's Hospital Research Full time Temporary Date posted: Shift/ hours of work: Research Data Analyst The ASIST Project, led by neurosurgeon Dr.

Christopher

Smith, is dedicated to advancing innovative AI-driven tools that enhance clinical workflows and improve patient outcomes. Our team is currently looking for a Research Data Analyst . The primary responsibility of the Data Analyst in this position is to design and develop advanced artificial intelligence models using medical imaging data, with a focus on supporting clinical decision-making in emergency and trauma care.

This involves conceptualizing and implementing scientifically rigorous modeling approaches, selecting and applying appropriate analytical techniques, and translating complex imaging and clinical data into actionable insights.

Key responsibilities include designing algorithms and study methodologies, developing and validating statistical analysis plans, performing and interpreting analyses, and communicating results in a clear, practical manner to clinicians, researchers, and other stakeholders to improve patient outcomes in critical care settings. Data Analyses, Statistical Modeling, and Machine Learning (40% of work time) Follow detailed study protocols and analysis plans to perform a wide variety of statistical analyses, including: Design, implement, and validate advanced deep learning models for medical imaging data, with a focus on emergency and trauma applications. Develop and optimize 3D convolutional neural networks (CNNs), vision transformers (ViTs), and other modern architectures for clinical decision support.

Apply and evaluate a wide range of modeling techniques, including: Multimodal data integration (imaging, clinical, and demographic data). saliency maps, Grad-CAM). Conduct rigorous model validation using cross-validation, external datasets, and real-world clinical data. Carry out data analyses using statistical and machine learning techniques, including supervised, unsupervised, and reinforcement learning.

Develop and apply predictive models and risk scores using algorithms such as linear/logistic regression, survival analysis, PCA, GLM, GAM, GEE, SVM, random forests, neural networks, and time series models (using R or Python libraries). Apply natural language processing (NLP) methods to unstructured text data, including bag-of-words, topic modeling (e.g.,



Optimize models through hyperparameter tuning and evaluate performance using appropriate metrics (e.g., Document all modeling workflows, code, and iterations with proper commenting and version control (e.g., Deploy models to production in collaboration with DevOps teams and establish systems to monitor and maintain model performance post-deployment. Data Exploration, Preparation, and Visualization (30% of work time) Ensure adequate quality control by setting standards, monitor results and institute appropriate steps for data cleaning, consistency checks and other data quality control measures prior to analysis.

Maintain data documentation, physical and logical storage of scripts, records and master archive lists. Perform descriptive and inferential descriptive analysis in R and/or Python. Write HTML/PDF/Microsoft Word reports summarizing the analysis.

Validate output tables, listings or figures generated to ensure accuracy and reliability of analyses. Pre-process raw data to prepare for analysis. This includes cleaning and merging data from multiple sources, as well as understanding overall data quality.

Produce high quality ad hoc and standardized reports, customized per project using R/Python procedures, tailored to different end users (e.g., clinicians, senior management, and hospital executives). Develop efficient programs, algorithms, or systems to reduce programing time of standardized data analyses and reports.

Develop Project Analytic Plans Outlining Key

Components of Analytical Approaches (15% of work time) Work closely with colleagues and research partners to establish coding techniques, structure of dataset for studies and develop sound analytical plans. Work with other team members to understand which analytical approach would be best suited to answer the project objectives. Meet regularly with the project team to provide updates on project status and present results.

Write project proposals and detailed analytic plans. Understand data requirements based on stated project goals. Writing data reports containing the results of analyses. Providing recommendations based on results of analyses and project objectives.





Documenting and communicating errors in data/code to senior staff. Strict compliance with patient/employee confidentiality practices and policies. Appropriate identification, reporting and response to patient/employee confidentiality breaches in accordance with established policies and procedures.

Appropriate identification, reporting and response to patient/employee safety risks and incidents/events in accordance with established policies and procedures. Bachelor’s degree in mathematics, statistics, biostatistics, computer science, or related discipline with at least 1 year of professional data science experience OR demonstrable equivalent combination of specialized education and experience. Ability to analyze and problem solve in the areas of data management and preprocessing, modeling, and evaluation, with consultation as needed.

Intermediate experience (4-5 years) with all of the following SQL, R and/or Python. Fully proficient in the use MS Office software (Word, Excel, PowerPoint, Outlook, Internet Explorer, etc.). Is comfortable designing and implementing medical imaging AI models using R/Python libraries under minimal supervision; Is comfortable documenting code and using version control systems such as Git under minimal consult.

Is proficient in using common data visualization libraries from R or Python (Plotly, ggplot, matplotlib, etc.). Can build data visualizations using D3 libraries or open-source equivalents (e.g., highchart) and can prepare and automate data reports in RMarkdown or Jupyter notebooks with minimal consult. Must be able to read in and merge data from disparate sources, perform data quality checks, manage missing data, and prepare data for machine learning models under minimal supervision.

Experience with unstructured data sources.

Experience preparing data for varied statistical methods preferred.

Experience with clinical data in a healthcare setting is a plus. Ability to analyze and problem solve in the areas of data management and preprocessing, modeling and evaluation, with consultation as needed. Excellent organizational skills to manage multiple tasks in a timely manner, project management skills would be an asset.

We strive to provide a recruitment process that is barrier-free and in compliance with the Accessibility for Ontarians with Disabilities Act (AODA) and the Ontario Human Rights Code. We understand that you may require an accommodation at any stage of the recruitment process.

📌 Research Data Analyst Neurotrauma (Toronto)
🏢 St. Michael's Hospital
📍 Toronto