Philips, Internship: Data Science for Multidimensional Market Modelling

• Analyse the existing market segmentation methodology, datasets and assumptions and translate the business challenge into a mathematical and statistical modelling framework.
• Research and evaluate suitable statistical and mathematical approaches for multidimensional market reconciliation such as iterative proportional fitting, constrained optimization, entropy-based methods, and Bayesian/probabilistic approaches.
• Develop and validate a model that combines existing estimates with multiple market observations, taking differences in data availability and confidence into account.
• Design the methodology to dynamically incorporate new information while maintaining a coherent overall market view.
• Establish appropriate validation methods to assess model accuracy, stability and robustness.
• Document the methodology and translate analytical findings into clear conclusions for business stakeholders.

Other location: Best

You are currently pursuing a Bachelor's or Master's degree, preferably in Data Science, Econometrics, Applied Mathematics, Statistics, Operations Research, Artificial Intelligence, Computer Science, Engineering, or another strongly quantitative discipline.

You bring:

• A strong foundation in mathematics, statistics and quantitative modelling.
• Knowledge of statistical methods, preferably including optimization, probabilistic modelling or multidimensional data analysis.
• The ability to structure, transform and analyse large and complex datasets.
• Strong analytical and problem-solving skills with attention to data quality, model robustness and reproducibility.
• The ability to explain complex quantitative concepts clearly to non-technical stakeholders.
• Good written and verbal communication skills in English and a collaborative mindset.

This assignment will encounter a variety of structured & unstructured data sources and experience with Excel, SQL, Python, R, Databricks, Power BI, machine learning or optimization techniques is an advantage. Previous healthcare or medical technology experience is not required.