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.

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📌 Demand Forecasting Applied Scientist (Winnipeg)
🏢 Kinaxis
📍 Winnipeg