Βασικό

On Lead Data Scientist (Supply Chain Forecasting)

Zürich, Zurich, Switzerland Εταιρεία: TN Switzerland Πελάτης / Εργοδότης: On
Δημοσιεύτηκε: 18.05.2026
Καταληκτική ημερομηνία: 02.07.2026
Αναφορά εργασίας: 2b52680c292f716fe4270b8c37c4d8b2

Πληροφορίες εργασίας

Τοποθεσία
Zürich, Zurich, Switzerland
Εταιρεία
TN Switzerland
Πελάτης / Εργοδότης
On
Αναφορά εργασίας
2b52680c292f716fe4270b8c37c4d8b2
Τύπος καταχώρησης
Βασικό
Απαιτείται άδεια εργασίας της ΕΕ
Όχι
Δημοσιεύτηκε
18.05.2026
Καταληκτική ημερομηνία
02.07.2026

Περιγραφή καθηκόντων

Job Details 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.Meet The TeamYou 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.What We OfferOn 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.

Δεξιότητες

apply blended learning apply for research funding apply research ethics and scientific integrity principles in research activities build recommender systems Business Analytics Business Intelligence collect ICT data communicate with a non-scientific audience Computational Biology Computer Simulation conduct research across disciplines create data models Data Engineering data ethics Data Mining Data Models data quality assessment Data Science data visualisation software define data quality criteria deliver visual presentation of data demonstrate disciplinary expertise design database in the cloud design database scheme develop data processing applications develop professional network with researchers and scientists Digital Curation disseminate results to the scientific community draft scientific or academic papers and technical documentation empirical analysis establish data processes evaluate research activities execute analytical mathematical calculations Hadoop handle data samples Healthcare Analytics image recognition implement data quality processes increase the impact of science on policy and society information categorisation Information Extraction integrate gender dimension in research integrate ICT data interact professionally in research and professional environments interpret current data LDAP LINQ make data-driven decisions manage data manage data collection systems manage findable accessible interoperable and reusable data manage ICT data architecture manage ICT data classification manage intellectual property rights manage open publications manage personal professional development manage research data Marketing Analytics mathematical modelling MDX mentor individuals multidisciplinary research N1QL normalise data online analytical processing operate open source software perform data cleansing perform data mining perform project management perform scientific research promote open innovation in research promote the participation of citizens in scientific and research activities promote the transfer of knowledge publish academic research quantitative analysis query languages report analysis results Research Design resource description framework query language Scientific Computing scientific literature Social Network Analysis SPARQL speak different languages State Estimation statistical modeling techniques Statistics synthesise information teach in academic or vocational contexts think abstractly Unstructured Data use data processing techniques use databases use spreadsheets software visual presentation techniques write scientific publications XQuery

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