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.

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