Senior Scientist (Data Science & AI)

TL;DR

Senior Scientist (Data Science & AI): Building and shipping scalable data science applications to optimize chemical and biochemical manufacturing processes with an accent on model-driven approaches for plant engineers. Focus on implementing MLOps, processing time-series data, and integrating physics-based modeling to improve yield and sustainability.

Location: Delft (Netherlands) or Geneva (Switzerland)

Company

A global leader in nutrition, health, and beauty, leveraging science and creativity to optimize biochemical manufacturing operations.

What you will do

• Design and deploy scalable data science applications for manufacturing, from initial concept to validated product.
• Implement data-driven models that assist plant engineers and operators in daily decision-making.
• Collaborate with multi-disciplinary teams of engineers and data scientists to optimize yield, throughput, and sustainability.
• Convert complex data insights into measurable operational impact and KPIs.
• Drive a data-driven mindset across sites and establish best practices for coding and MLOps.
• Research and implement state-of-the-art methods in industrial process analytics.

Requirements

• PhD or equivalent experience in (Bio)Chemical Engineering, Data Science, Statistics, or Computer Science.
• 3-7 years of industrial or academic experience in manufacturing data science, preferably in chemical processes.
• Strong expertise in Machine Learning with a focus on real-world validation and pragmatic industrial application.
• Proficiency in Python and the core Data Science stack for time-series forecasting and multivariate modeling.
• Ability to create end-to-end computational workflows from data ingestion to deployment.
• Experience with software engineering best practices: git, Docker, CI/CD, and unit testing.

Nice to have

• Experience with process analytics tools like Seeq or TrendMiner.
• Knowledge of causal inference, Bayesian methods, and drift detection.
• Expertise in physics-informed (gray-box) models, PINNs, or digital twins.
• Familiarity with GenAI, LLMOps, and Vision Language Models.
• Experience with AWS, Azure, or Databricks.

Culture & Benefits

• Opportunity to have a direct impact on global manufacturing sustainability and operations.
• Access to an experienced global Advanced Analytics community.
• Supportive environment with room for expertise growth in both ML and manufacturing.
• Culture of inclusion, belonging, and equal opportunity.

Hiring process

• Online application via the career portal.
• Submission of a resume in English.