Machine Learning Scientist
Montreal (in-person)Full-timePosted 1mo ago
About the role
Applied Machine Learning Scientist role focusing on solving real-world, imperfect datasets with emphasis on scientific problem solving, model development, validation, and production-aware analyses; on-site in Montreal.
Responsibilities
- Explore datasets and understand the underlying data-generating processes.
- Develop, evaluate, and improve machine learning, signal processing, and statistical models.
- Perform feature engineering, model selection, validation, and error analysis.
- Identify issues such as confounding, data leakage, measurement variability, and distribution shift.
- Design experiments and analyses to resolve uncertainty and guide modelling decisions.
- Investigate new modelling approaches, including classical ML and deep learning (when appropriate).
- Produce clear, reproducible Python code that isn’t limited to notebooks, and communicate findings to technical and non-technical stakeholders.
- Develop analyses and models with the expectation that it will be deployed into production.
- Investigate model performance and failures using real-world production data.
- Perform ongoing error analysis, diagnostics, and root-cause investigations.
- Identify distribution shifts, edge cases, systematic biases, and degradation in model performance.
- Translate production observations into experiments, improvements, or data-collection strategies.
Qualifications
- Bachelor's degree (Master’s or PhD preferred) in Engineering, Computer Science, Data Science, Mathematics, or a related field
- minimum of 5 years of professional experience excluding internships
- Strong foundation in machine learning fundamentals, statistics, and experimental reasoning
- Strong Python skills and experience with common ML/data science libraries
- Ability to work independently on ambiguous problems and determine what questions need to be answered
- Good understanding of model validation, uncertainty, bias/variance, and generalization
- Ability to distinguish between improvements that are statistically or scientifically meaningful and those that simply improve a metric
Skills
Required:Machine LearningPythonExperimentation & ValidationData Analysis
Benefits
- Health insurance (medical, dental, vision, and more)
Last updated Aug 30, 2026. Interested? Apply on the company site.
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