Lead the application of machine learning techniques (e.g., regression, classification, time-series forecasting) to solve complex business problems across domains such as product development and advanced analytics
Own the preparation of complex datasets, including data cleaning, transformation, and structuring, to enable robust modeling and high‑quality analysis.
Partner closely with domain experts and cross‑functional stakeholders to design, develop, and deliver impactful data science solutions aligned with business needs.
Deploy and operationalize models in production environments, ensuring performance, reliability, and scalability, using platforms such as Azure ML, Databricks, and Snowflake.
Monitor model performance and continuously optimize accuracy, robustness, and scalability over time.
Translate analytical insights into clear visualizations and structured narratives, effectively communicating recommendations to both technical and non‑technical audiences.

Advanced degree (MSc or higher) in Data Science, Statistics, Computer Science, or a related field
Extensive experience in data science within Life Sciences, Food, or Academia, applying agile development practices
Proven track record in building and deploying predictive models in production
Hands-on expertise with ML frameworks (TensorFlow, Keras, PyTorch, Scikit-learn) and statistical methods including Design of Experiments
Familiarity with APIs (REST, JSON) and data visualization tools such as Power BI, PowerApps, and Streamlit
Proficiency with cloud and data platforms including Azure, Databricks, Snowflake, and SQL databases.
Ability to explain complex technical concepts to non-technical audience
Strong collaboration skills, with experience working closely with cross-functional teams (scientists, sensory specialists, product developers)
Highly autonomous and self‑driven, with strong problem‑solving capabilities
Excellent communication skills in English.

Exciting opportunities to develop your career your way; across different brands, businesses, functions, and regions.
Flexible working arrangements
facilitating creativity and collaboration
A culture of respect, with diversity, equity and inclusion at its core.
A dynamic international environment empowering you to learn, develop and grow.

Data Science Specialist

Key skills