Demand forecasting and machine-learning rigor define this Senior Staff Applied Scientist opportunity at Kinaxis. Canadian locations offer hybrid or work from home arrangements.

This hands-on individual-contributor role owns scientific strategy for forecasting across enterprise supply-chain applications. You will translate business goals into machine-learning problems, mentor senior specialists, and strengthen evaluation practices. The platform must support millions of series and daily forecasts.

Key Responsibilities:

- Set forecasting science agendas and technical priorities
- Mentor senior scientists and machine-learning engineers
- Evaluate hierarchical, intermittent, and domain-adapted forecasting
- Define reproducible experiment-to-validation practices
- Align accuracy, scale,



cost, and commercial priorities

Requirements:

- Expertise in statistical, modern machine-learning, and deep-learning methods
- Strong knowledge of calibration, uncertainty, covariates, and evaluation
- 8+ years testing, debugging, and optimizing Python machine-learning solutions
- Proficiency with Spark, GCP or Azure, containers, and distributed computing
- Ability to influence roadmaps across multiple teams

Bring demand forecasting depth, scientific judgment, and cross-team influence to Kinaxis's machine-learning platform.

📌 Demand Forecasting Applied Scientist (Quebec City)
🏢 Kinaxis
📍 Quebec City