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Lead Data Scientist (Supply Chain Forecasting)

On AG -
Zürich, ZH

Soumettre votre candidature

Détails de l'emploi

Qualifications

Niveau Doctorat
Niveau Master
SQL
Technologies de l'information
Python

Description complète du poste

Location: Zurich

Technology

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.

About the Team

You will join a high-performing, interdisciplinary team of data scientists and engineers dedicated to driving a significant impact on our supply chain through data, ML, and AI. We operate in a fast-paced environment where technology is viewed as an innovation advantage rather than a support function. We work together to solve complex logistics challenges. We value "Pragmatic Visionaries" who take pride in high quality technology and are excited by the challenge of moving physical products more efficiently across the globe.

Zürich

Just by the banks of the Limmat you’ll find our largest global hub in Zürich West – On Labs – where you can hike up 12 floors through our custom-built spiral trail.

Förrlibuckstrasse 190,
8005
Switzerland

Location

What we offer

On is a place that is centered around growth and progress. We offer an environment designed to give people the tools to develop holistically – to stay active, to learn, explore and innovate. 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.

On is an Equal Opportunity Employer. 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.

Build the better you

What to expect

We want to set everyone up for success, so here’s the lowdown on how we hire. Our process is a two-way street – bringing you into our culture, while helping us learn how you think.

Our full process can last about eight weeks from application to offer, because we care about getting it right. These steps explain how we usually do things.

Before you get started, feel free to consider if you want to work with us. Strange question? Well, we give people a lot of space to navigate their day-to-day and that style isn't for everyone. We want you to be passionate about what you do and be sure this is the right fit. Because when skills and passion combine – it creates that 'Wow' moment.

Step One

It starts with you...

You'll start by submitting your application to a specific role. We try to keep this step as simple as possible. We do get a lot of applications, but we review them all. If you're a good fit to the role, a recruiter will follow up with you directly. If you didn't receive a reply, or were unsuccessful this time around, we encourage you to look for other possible matches at On.

Step Two

Interview with a recruiter

What ignites your spirit? This is where we’ll start getting to know all about you and what makes you tick – and it’s your first chance to get a feel for our culture. Chatting with a member of our talent team, you’ll learn more about On and how we work. We’ll learn about what motivates you and what you could bring to the team.

Step Three

Interview with a hiring manager

Ready to dig into the details? This second interview will be held with your future manager and will focus on the specifics of the job. Together you’ll delve into your unique skills and experiences and how they could be relevant at On. It's also a time to assess how you might feel working side-by-side. Bring any questions you have about the job, the team or anything else you might like to know – this is an open forum.

Step Four

The Case Study

What's your style? This task will help us understand how you think, face a challenge and give insight into your novel ideas. Designed to give everyone their best shot, your case study is based on something you might typically experience on the job. This is your chance to show us what you’ve got. So express yourself. Be you.

Step Five

The Experience Day

Your first taste of the Oniverse. This is a time to meet some of the people you'll be working closest with. In person or virtually, you'll get a feel for the day-to-day at On and the people who make it happen. You'll chat with a few potential teammates - the conversations will be as equally driven by the role and your experience as by our values. We believe how you do things is just as important as what you do.

Step Six

The Result

Are we a good fit? We’ll get together internally to share our feedback and decide if we’re a match. We know that job searching is a big time investment, so it’s not a decision we take lightly. It’s also time for you to reflect on the experience – are we the right place for you? No matter the outcome, we’ll give you meaningful feedback.

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algorithm engineer emplois - zürich, zh

Lead Data Scientist (Supply Chain Forecasting)

Tech Lead Manager, Freshness and Factuality, GeminiApp, DeepMind

Tech Lead: Manufacturing Intelligence

More jobs to discover

Je souhaite recevoir la dernière alerte Emploi pour les postes de ce type : algorithm engineer (zürich, zh)

Related Searches

Technology

In short

Your Mission

Your story

About the Team

Zürich

What we offer

What to expect

Step One

It starts with you...

Step Two

Interview with a recruiter

Step Three

Interview with a hiring manager

Step Four

The Case Study

Step Five

The Experience Day

Step Six

The Result

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