Scientist Machine Learning***Scientifique en apprentissage automatique

IPEX is one of the North American leading providers of advanced plastic piping systems. Our mission is to shape a better tomorrow by connecting people with water and energy.

We currently have an exciting opportunity for an Scientist, Machine Learning.

This role is an Hybrid position, with expectations to be onsite in our offices in Oakville, Tuesday, Wednesday and Thursday.

Do not miss the opportunity to join a diverse group of people-centric professionals, thought leaders and rapid thinkers, entrepreneurs in spirit and status quo-fighters!

Job Summary

The Applied Machine Learning Scientist develops, validates, and operationalizes machine-learning and statistical solutions that improve supply-chain decisions. The role is primarily focused on demand forecasting, inventory optimization, and related decision-support problems. The successful candidate will combine strong applied modelling skills with the ability to work independently in Python and SQL, build reliable model-ready datasets, and translate experiments into maintainable production solutions. The role works closely with the Manager of Advanced Analytics & Machine Learning, and with business and technical stakeholders to ensure solutions are measurable, explainable,scalable, and aligned with operational constraints.

Key Responsibilities:

Applied Modelling & Experimentation

• Develop and improve forecasting and optimization models for supply-chain and operational use cases.

• Perform feature engineering, model selection, hyperparameter tuning, error analysis, and structured experimentation.

• Design evaluation frameworks using time-aware validation, backtesting, and business-relevant performance metrics.

• Apply appropriate statistical and machine-learning methods, including time-series analysis, regression, probabilistic modelling, and tree-based models.

• Investigate model bias, uncertainty, drift, and failure modes, and recommend practical improvements.

Productionization & Data Workflows

• Write clear, maintainable, production-quality Python and SQL.

• Build and maintain scalable model workflows and model-ready datasets using Snowflake and collaborative analytics environments such as HEX.

• Operationalize model outputs through reliable data pipelines, versioning, monitoring, retraining, and alerting practices.

• Contribute to shared coding, testing, documentation, and model-governance standards.

Project Execution & Collaboration

• Own defined modelling workstreams from problem formulation through validation, implementation, and business adoption.

• Partner with Supply Chain, IT, Data, and other stakeholders to define objectives, constraints, and success measures.

• Present technical findings clearly and translate model results into actionable business recommendations.

• Evaluate emerging methods and technologies based on their practical value to current business problems.

Qualifications & Experience

Education & Experience

• Master's degree in Data Science, Statistics, Computer Science, Mathematics, Operations Research, or a related quantitative field; or a bachelor's degree with equivalent applied machine-learning experience.

• Three or more years of applied data-science or machine-learning experience, including meaningful ownership of a production modelling solution.

• Demonstrated experience taking a modelling problem from raw data through feature engineering, validation, implementation, and performance review.

Required Technical Skills

• Strong Python skills, including practical use of pandas, NumPy, scikit-learn, and gradient-boosting libraries such as LightGBM or XGBoost.

· Strong SQL skills and the ability to independently create, validate, and troubleshoot large analytical datasets. · Strong foundation in statistics, experimental design, time-series validation, model evaluation, and leakage prevention.

• Ability to design solutions that respect real operational constraints and balance model performance with maintainability and adoption.

• Clear written and verbal communication with both technical and business audiences.

Preferred Assets

• Experience with demand forecasting, inventory, supply-chain analytics, manufacturing, or operations research.

· Experience with Snowflake or another modern cloud data platform. · Familiarity with Git, automated testing, model versioning, monitoring, and reproducible ML workflows.

• Exposure to MLOps, deep learning, or generative AI where relevant to an applied business problem.

• Credentials or practical knowledge in operations, supply chain, Lean, or CPIM are an asset.

The compensation for this position is between $91,300 and $110,000 annually, based on experience and qualifications.

IPEX is committed to providing accommodations for people with disabilities throughout the recruitment process and, upon request, will work with qualified job applicants to provide suitable accommodation in a manner that takes into account the applicant’s accessibility needs due to disability. Accommodation requests are available to candidates taking part in all aspects of the selection process for IPEX jobs. To request an accommodation, please contact HR at [email protected]