Data Scientist

Here's a brief overview of the tasks and responsibilities you'll have :

• Analyze large and complex data sets to identify trends, opportunities, and actionable insights to support strategic and operational decisions;
• Design and validate statistical models and machine learning algorithms for predictive, descriptive, and prescriptive analytics use cases;
• Collaborate with business partners to define analytical issues, success criteria and translate business needs into data science solutions;
• Develop end-to-end data science workflows, from data exploration and preparation to model training and evaluation;
• Work with data and AI specialists to bring models into production and ensure scalability, performance, and reliability;
• Conduct experiments, including A/B testing and causal analysis, to measure impacts and support data-driven decision-making;
• Interpret and communicate analytical results clearly to technical and non-technical audiences through presentations, dashboards and documentation;
• Ensure data quality, reproducibility of analyses, and compliance with data governance, privacy, and responsible artificial intelligence standards;
• Contribute to documentation, best practices, and knowledge sharing through wikis, guides, and analytical standards;
• Keep up-to-date on advances in data science, machine learning, and analytical methods, and proactively propose new approaches or improvements.

The profile you are looking for is as follows:

• Hold a bachelor's, master's or doctoral degree in data science, statistics, computer science, engineering, mathematics, economics or a related quantitative field;
• Have a minimum of three (3) years of experience in data science, advanced analytics, or a related role, with a proven track record on business objectives;
• Have programming experience with Python and SQL as well as data manipulation and analysis libraries such as pandas, NumPy, and scikit-learn;
• Master the fundamentals of statistics, probability, and machine learning techniques, including regression, classification, clustering, and time series;
• Be familiar with feature engineering, model evaluation, and model interpretability;
• Use Databricks, its notebooks, and workflows to process and analyze large data sets;
• Understand the benefits and limitations of distributed computing with Apache Spark;
• Use Git and Azure DevOps, or an equivalent tool such as Jira, to track development and coordinate projects;
• Demonstrate proficiency in data visualization and storytelling using tools such as Power BI, Tableau or equivalent libraries;
• Make clear and relevant prescriptive recommendations rather than being limited to descriptive observations;
• Possess knowledge of experimentation frameworks and causal inference concepts;
• Ability to translate complex analytical results into clear and actionable findings;
• Demonstrate a strong ability to collaborate with stakeholders, challenge assumptions, and influence decisions using data;
• This position requires fluency in French and English for daily tasks, understanding documentation, and professional communication with customers, suppliers, and colleagues across Canada. French and English language skills are essential, both oral and written.