Data Science Intern: DoE & Modelling for Industrial R&I

Danone; Utrecht; Hybrid; EUR 6,600 - 7,900; Full time

Benefits offered by this job

650 EUR internship allowance

Home working allowance

Public transport travel card

Career development workshops

International environment

Internship community

Job summary

Danone NL is offering a Data Science Intern position in Utrecht focusing on Design of Experiments and modelling. You will explore DoE methods and modelling-based experimentation to improve planning and decision-making within the R&I team.

You will work on literature reviews, develop mathematical models, and compare DoE approaches, communicating findings to stakeholders. The program runs from November and lasts at least 6 months with hybrid work.

Qualifications

• Enrolled as a Master’s student for the full duration of the internship.
• Must reside in the Netherlands with a valid BSN number; non-EU citizens need Dutch residency and a three-party agreement with Danone.

Responsibilities

• Review literature on DoE and modelling approaches for planning efficient experiments.
• Identify and categorize experimental challenges in industrial R&I.
• Develop mathematical models for various experimental problems.
• Use models as virtual experiments to evaluate DoE and model-guided approaches.
• Compare performance under non-linearity, interactions, noise, and resource constraints.
• Translate findings into practical guidance for DoE or modelling-based experimentation.
• Document and present results to stakeholders.

Skills

Motivated

Enthusiastic

Communication skills

Proactive

Initiative

Education

Master's student (Data Science/Statistics/Applied Mathematics/Engineering)

Tools

Python

R

MS Office

Job description

Danone NL is offering a Data Science Intern position in Utrecht focusing on Design of Experiments and modelling. You will explore DoE methods and modelling-based experimentation to improve planning and decision-making within the R&I team.

You will work on literature reviews, develop mathematical models, and compare DoE approaches, communicating findings to stakeholders. The program runs from November and lasts at least 6 months with hybrid work.