Associate Data Scientist
Role overview
VF Corporation is looking for a Associate Data Scientist to join our team in Stabio, Switzerland.
Let’s talk about the role!
As an Associate Data Scientist at VF Corporation, you will focus on demand forecasting for our fashion and retail business: anticipating what consumers will buy, where and when, across brands, channels and markets, including products and stores with little or no sales history.
Responsibilities
- check_circle Demand forecasting: build forecasting models at product, size, store, channel and market level across Wholesale and Direct-to-Consumer, supporting buying, allocation, replenishment and planning.
- check_circle Cold-start forecasting: contribute to the team's work forecasting demand for new products, collections, stores and markets with no sales history, a core challenge in fashion and central to this role.
- check_circle State-of-the-art methods: benchmark and productionize zero-shot and foundation models for time series against classical and machine learning baselines.
- check_circle Collaboration: contribute to AI and Generative AI use cases, help monitor deployed models, and work with Data Engineers, DevOps, Product, Planning and Merchandising to drive adoption, presenting results and their limitations clearly to stakeholders.
Basic qualifications
- Required Background: Bachelor’s degree (Master’s a plus) in Data Science, Statistics, Computer Science, Engineering or a related field, with around 1-2 years of experience in Data Science and forecasting.
- Industry Background: experience in fashion, apparel or retail with exposure to demand planning, merchandising or supply chain is a strong plus.
Preferred qualifications
- Demand Forecasting in Fashion and Retail: hands-on experience with short product lifecycles, strong seasonality, promotions and markdowns, size and colour curves, sparse demand and hierarchical forecasting.
- Cold-Start Forecasting: attribute- and similarity-based approaches, product embeddings, like-for-like matching, transfer learning and pre-season planning.
- Zero-Shot and Foundation Models for Time Series: up-to-date knowledge of the state of the art (e.g., TimeGPT, Chronos, TimesFM), and the ability to benchmark zero-shot versus fine-tuned performance against strong baselines.
- Time Series Foundations: statistical (ARIMA, ETS, Croston), machine learning and deep learning (e.g., Gradient Boosting, DeepAR, N-BEATS, N-HiTS) approaches, plus probabilistic forecasting, backtesting and metrics such as WMAPE and MASE.
- Python and ML Libraries: strong Python with pandas, NumPy, scikit-learn, PyTorch or TensorFlow, and forecasting libraries such as statsmodels, StatsForecast, NeuralForecast.
- Statistics and SQL: core ML concepts, hypothesis and A/B testing, hyperparameter optimisation, and efficient SQL on large-scale structured data.
- Generative AI basics: how LLMs are applied in practice (prompting, embeddings, RAG).
Benefits
- check_circle A supportive feedback-based culture where respect and integrity guide us in what we do
- check_circle An inclusive international environment where people of diverse backgrounds, lifestyles and nationalities love working together
- check_circle Be part of an iconic lifestyle brand in a multi brand, multi countries organization
- check_circle On site gym offering health and well-being initiatives
- check_circle A discount card with 50% on all VF brands
- check_circle Break out areas offering complimentary hot drinks
About the company
As an equal opportunity employer, we strive to foster a culture of belonging based on respect, connection, openness and authenticity. We are committed to building and maintaining a workplace that celebrates the diversity of our associates, allowing them to bring their authentic selves to work every day.
Tags & Focus Areas
About VF Corporation
Ready to Join the Team?
Apply once with DevFound — we route your profile to VF Corporation and keep you posted on matching AI roles.