Data Scientist AIML

Job description:

DATA SCIENTIST

Remote (Offshore – Outside Canada)

Work Schedule: The position operates on a bank of hours system, with a target average of 35 hours per week. Weekly hours may vary (more or less than 35 hours) depending on operational needs but will average out to 35 hours/week over the duration of the contract.

Contract Duration: 12-month mandate.

JOB DESCRIPTION

We are focused on building a highly talented and ambitious team from the ground up that revolutionizes the way we work around Data & Analytics . We are a team that has the potential to unlock tremendous value for the organization and you have the unique opportunity to be part of it from the beginning.

You will join central Data & Analytics team as a Data Scientist and bring your analytical skills and business insight to our dynamic team.

This role is perfect for someone who seeks to blend their understanding of business intelligence with the predictive power of data science to unlock new opportunities.

YOUR KEY RESPONSIBILITIES

• Design, implement and productionize machine learning models and pipelines within an MLOps framework (from prototyping to monitoring and retraining).
• Collaborate with Product Managers and stakeholders to translate business needs into measurable ML use-cases and success metrics.
• Work hands-on in Python for exploratory analysis, model building and production code (clean, tested, versioned).
• Implement model monitoring, drift detection, alerting, and model performance dashboards.
• Contribute to model explainability, fairness audits, and bias mitigation where applicable.
• Apply rigorous A/B testing & experimentation or causal inference to validate business impact.
• Stay current with ML/AI developments (including foundation models / LLM use cases), evaluate and industrialize relevant advances.

YOUR QUALIFICATIONS AND SKILLS

• MSc (preferred) or BSc in Statistics, Data Science, Computer Science, Mathematics, Engineering, Economics or equivalent.
• ~3–6+ years of hands-on experience in data science / ML, ideally with production ML or MLOps exposure.
• Strong Python skills and a track record of shipping production-grade code (pandas, numpy, scikit-learn, comfortable with Deep Learning framework (PyTorch, TensorFlow).
• Solid SQL skills and experience working with Data Warehouse (Snowflake is a plus).
• Experience with at least one end-to-end analytics / ML platform (Dataiku, DataBricks, Vertex, SageMaker)
• Familiarity with common MLOps tools (experiment tracking, model registry, CI/CD).
• Practical experience with model monitoring, retraining strategies, and observability.
• Clear communicator, able to explain technical tradeoffs to non-technical stakeholders.
• Comfortable in French (spoken/written), team communication is primarily in English; strong English proficiency is required.