Senior Data Scientist – Medical Imaging AI

About the role

We are seeking a Senior Data Scientist to advance our AI models for radiology, covering chest X‑ray, musculoskeletal, and CT imaging. You will work at the intersection of computer‑vision research and real‑world clinical application, where model decisions directly impact radiologists and patient diagnoses.

Key responsibilities

• Design, train, and validate machine‑learning and deep‑learning models for medical‑imaging use cases.
• Own the full model lifecycle: data preparation, architecture selection, training, evaluation, and deployment support.
• Collaborate with product, engineering, and regulatory teams to translate clinical and business requirements into functional models.
• Handle large, messy imaging datasets, addressing class imbalance, edge cases, and label noise.
• Stay current with state‑of‑the‑art computer‑vision research and apply relevant advances.
• Explain model behavior, performance, and limitations to both technical and non‑technical stakeholders.
• Contribute to internal knowledge‑sharing and mentor junior team members.
• Support regulatory and quality documentation in a medical‑device environment.

Required profile

• 5+ years of hands‑on experience as a Data Scientist or Machine Learning Engineer with end‑to‑end model ownership.
• Strong analytical mindset and ability to communicate complex results clearly.
• Fluent English and a degree in Computer Science, Data Science, Statistics, Engineering or equivalent practical experience.

Required skills

• Python programming.
• Experience with modern ML/DL frameworks such as PyTorch or TensorFlow.
• Solid grounding in statistics, classical machine learning, and deep‑learning architectures (e.g., CNNs).
• SQL and data‑wrangling skills for large, imperfect datasets.
• Awareness of MLOps practices for moving models from research to production.

What we offer

• Gross salary between €65,000 and €80,000 per year.
• Opportunity to work on cutting‑edge AI solutions that directly influence clinical practice.
• Collaborative environment with cross‑functional product, engineering, and regulatory teams.