Demand forecasting and machine-learning rigor define this Senior Staff Applied Scientist prospect 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, 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.