Applied Scientist Intern

Responsibilities

• Explore and experiment with ML/AI approaches to solve POI-domain problems such as entity matching, address parsing, and data quality assessment
• Implement and evaluate models and algorithmic solutions on real-world, large-scale geospatial datasets
• Design and run experiments, analyze results, and translate findings into clear insights and recommendations
• Contribute to the development of data pipelines and tooling that support model training and evaluation
• Collaborate with Applied Scientists, Engineers, and Product stakeholders to integrate work into the broader team workflow
• Document experiments, methodologies, and results clearly to support knowledge sharing

Requirements

• Currently enrolled in a Master's programme in Computer Science, Data Science, AI, ML, or a related field
• Solid grounding in machine learning fundamentals, including supervised/unsupervised learning and feature engineering
• Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn
• Proficiency in Python and experience with data manipulation libraries like Pandas or NumPy
• Analytical mindset with the ability to design experiments and interpret results critically

Preferred Qualifications

• Experience with Spark or other big data processing tools
• Familiarity with NLP or embedding-based methods (e.g., Sentence Transformers, BERT-based models)
• Strong interest in geospatial data, POI systems, or location intelligence

About the Company

TomTom is a global leader in location technology, providing high-quality maps, real-time traffic information, and advanced driver assistance systems. We engineer the first real-time map to help carmakers, fleets, and tech innovators navigate the world more efficiently.