Demand forecasting and machine-learning rigor define this Senior Staff Applied Scientist opportunity at Kinaxis. Canadian locations offer hybrid or remote work 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, contemporary 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.