Lead Data Scientist Supply Chain Forecasting

In short

As a Lead Data Scientist specialized in Supply Chain Forecasting, your mission is to revolutionize how we move products globally by building the next generation of predictive systems. You will bridge the gap between bleeding-edge research—such as Time Series Foundation Models—and production-grade supply chain solutions. This is a role for an experienced forecasting expert who has experience in building forecasts that combine multiple approaches to drive metrics such as Forecast Accuracy, stockout % and On-Time-In-Full (OTIF) metrics.

Your Mission

• Drive impact on Forecast accuracy: use a range of modelling approaches, such as advanced techniques such as Time Series Foundation Models (e.g., Chronos, TimesFM) and multi-level forecasting frameworks, to drive improvements in forecasting accuracy.
• Build Scalable Solutions: Design and deploy end-to-end machine learning pipelines autonomously, utilizing agentic coding tools to accelerate prototyping and development.
• Optimize our Supply Chain: Collaborate with business, product management and analytics teams to define how forecasts and related data flow through our supply chain.
• Evaluate our approaches: Work with our analytics partners to ensure we’re focusing on the right optimization metrics and forecasting challenges.
• Harness New Architectures: Explore how forecasting algorithms can be paired with agentic decision making tools to both accelerate and improve decision making.
• Innovate: Actively research the best practices and bleeding edge of forecasting approaches and ensure On’s forecasting capabilities are delivering maximum impact.

Your story

• Extensive Experience: You have 5+ years of experience in data science, with a deep specialization in demand forecasting and optimization within supply chain or retail environments.
• Technical Mastery: You are an expert in Python and SQL, with a proven track record of building and maintaining production-grade models, preferably using GCP and Vertex AI.
• Advanced Modeling: You have hands-on experience with Time Series Foundation Models, hierarchical forecasting, and solving "cold start" problems for high-growth product lines.
• Agentic Proficiency: You are comfortable using agentic coding tools to enhance productivity and are familiar with LLM-based approaches for data science workflows.
• Collaboration: You have a strong track record of working with multi-disciplinary teams to drive high impact in complex environments.
• Engineering Mindset: You are an engineer at heart, prioritizing robust code, CI/CD, and MLOps principles to ensure model reliability in a global, 24/7 supply chain.
• Academic Foundation: You hold a Master’s or Ph.D. in a quantitative field (e.g., Computer Science, Mathematics, Statistics) and stay at the forefront of AI research.