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, 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 in Québec employer: Kinaxis
At Kinaxis, we pride ourselves on fostering a vibrant work culture that prioritizes innovation and collaboration, making it an exceptional place for Software Architects to thrive. With our headquarters in Ottawa, Canada, we offer flexible work options, mentorship programs, and a commitment to employee well-being, ensuring that you can grow your career while contributing to meaningful projects that impact global supply chains. Join us and be part of a team that values diversity, sustainability, and the pursuit of excellence.
