Lead Data Scientist (Supply Chain Forecasting)

Das ist der Job

Equal Opportunity Employer On is an Equal Opportunity Employer.

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Optimize our Supply Chain: Collaborate with business, product management and analytics teams to define how forecasts and related data flow through our supply chain. Collaboration: Strong track record of working with multi‑disciplinary teams to drive high impact in complex environments.

Benefits On is a place that is centered around growth and progress. Our distinctive approach combines a supportive, team‑oriented atmosphere, with access to personal self‑care for both physical and mental well‑being, so each person is led by purpose.

Overview 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.

Responsibilities Drive impact on Forecast accuracy: use a range of modeling 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. 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.

Qualifications Extensive experience: 5+ years in data science, with deep specialization in demand forecasting and optimization within supply chain or retail environments. Technical mastery: 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: Hands‑on experience with Time Series Foundation Models, hierarchical forecasting, and solving “cold start” problems for high‑growth product lines. Agentic proficiency: Comfortable using agentic coding tools to enhance productivity and familiar with LLM‑based approaches for data science workflows.

Engineering mindset: Engineer at heart, prioritizing robust code, CI/CD, and MLOps principles to ensure model reliability in a global, 24/7 supply chain. Academic foundation: Master’s or Ph.D. in a quantitative field (Computer Science, Mathematics, Statistics) and current with AI research.

We offer an environment designed to give people the tools to develop holistically—to stay active, to learn, explore and innovate. We are committed to creating a work environment that is fair and inclusive, where all decisions related to recruitment, advancement, and retention are free of discrimination. #J-18808-Ljbffr