Time-series and demand forecasting expertise drives this Senior Staff Applied Scientist role at Kinaxis. Work hybrid in Ottawa or Toronto, or remotely elsewhere in Canada. As a senior individual contributor, you will set scientific direction for Kinaxis forecasting. You will define research priorities, establish technical standards, and guide engineering and data-science teams. Your work will support accurate, explainable forecasting at enterprise scale. Key Responsibilities:

Define research roadmaps and measurable machine-learning success criteria Guide classical, probabilistic, machine-learning, and pretrained forecasting approaches Establish metrics, benchmarks, backtesting,



and quality gates Shape architecture supporting millions of daily forecast series Explain scientific trade-offs to technical and executive audiences Requirements:

Deep hands-on time-series or demand forecasting expertise Knowledge of hierarchical, intermittent, probabilistic, and quantile forecasting Master's degree; Ph.D. preferred in a quantitative field 8+ years developing complex machine-learning solutions in Python Experience moving research into measurable production systems Apply scientific leadership, forecasting rigor, Python, and scalable machine learning to Kinaxis demand forecasting.

📌 Senior Staff Time Series Scientist (Quebec City)
🏢 Kinaxis
📍 Quebec City