Job Title

Job Description

Start Date: as soon as possible

Duration: minimum 5 months

Type: Internship

Weekly Presence: 40h (minimum 32h)

Location: Amsterdam OR Best (3x per week)

Internship: Data Science for Multidimensional Market Modelling

At Philips, our purpose is to improve people’s lives through meaningful innovation. Philips Image Guided Therapy Systems (IGT-S) develops advanced image-guided therapy solutions that support physicians in the diagnosis and treatment of patients during minimally invasive procedures.

Within IGT-S, market and portfolio insights are an important foundation for strategic and commercial decision-making. The Marketing Insights & Analytics team integrates internal and external data sources to develop a comprehensive understanding of market size, market share, competitive performance and future market opportunities.

We are looking for a Data Science Intern to help further develop our market modelling capabilities. Our market models combine large amounts of information from different sources and perspectives. While reliable market information is available at different levels, the detailed intersections between these perspectives are often not directly observable. Your assignment will be to develop and validate a multidimensional market reconciliation model that combines these sources into one mathematically consistent market view.

Position within Philips

You will be part of the Marketing Insights & Analytics team within Philips Image Guided Therapy Systems (IGT-S). The team supports strategic and commercial decision-making through insights into markets, competition and commercial performance.

You will work closely with Marketing Insights & Analytics colleagues and other IGT-S stakeholders. This internship offers the opportunity to apply advanced data science and quantitative methods to a complex real-world business problem and contribute to the future IGT-S market intelligence methodology.

Your Assignment and Activities

During this internship, you will take ownership of an applied data science assignment with direct relevance to strategic market decision-making.

Your main activities will include:

• 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.

The objective is to deliver a validated methodology and working proof of concept that can provide the foundation for a scalable multidimensional market segmentation model.

You're the Right Fit If

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.

How we work together

We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week. Onsite roles require full-time presence in the company’s facilities. Field roles are most effectively done outside of the company’s main facilities, generally at the customers’ or suppliers’ locations.

Monthly full-time allowance between €500 - €700 gross, depending on your education level. If you need to relocate to The Netherlands specifically for the internship there will be a different allowance. Part-time internships receive the allowance pro-rata. 

Housing compensation, in case of relocating to the vicinity of the office, €300,- net if location is in the vicinity of Amsterdam, €255,- net for all other Philips locations. To be eligible, your usual home-work travel distance needs to be more than 50 km or 1.5 hours of travel time (one way). Afterwards, you need to provide the rental contract from your (new) landlord.

Travel compensation, if you are not eligible for a free public transport (OV chipkaart - student travel product); you can receive max. €192,- net depending on your location. Paid holidays per internship term.

About Philips

We are a health technology company. We built our entire company around the belief that every human matters, and we won't stop until everybody everywhere has access to the quality healthcare that we all deserve. Do the work of your life to help the lives of others.

• Learn more about our business.

• Discover our rich and exciting history.

• Learn more about our purpose.

If you’re interested in this role and have many, but not all, of the experiences needed, we encourage you to apply. You may still be the right candidate for this or other opportunities at Philips. Learn more about our commitment to diversity and inclusion here.

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