)
)
Principal AI Scientist (m/f/x)
Tasks:
Project Level Activities
Provide subject matter expertise in the design and evaluation of scalable approaches for Whole-Slide Image (WSI) integration from external platforms into internal big data environments, including recommendations for data quality, integrity verification and handling of different WSI formats.
Develop and assess concepts for the de-identification of WSI-related data, including metadata, filenames and embedded information, ensuring alignment with applicable privacy and compliance requirements.
Provide expertise on dataset governance, data versioning and traceability concepts, including recommendations regarding dataset registries, training and validation split management, model lineage and reproducibility standards.
Conduct technical reviews and assessments of AI/ML architectures, data processing workflows and implementation approaches, providing recommendations to support scalable and scientifically robust solutions.
In General
Deliver expert analysis, technical assessments, recommendations and project-specific deliverables in accordance with agreed timelines and project objectives.
Contribute subject matter expertise on state-of-the-art AI/ML methodologies, reproducible research practices and industry best practices to support high-quality project outcomes.
Provide technical review and advisory support regarding deliverables from external vendors and project partners, where required.
Advise project stakeholders on relevant regulatory, compliance and quality considerations applicable to AI/ML solutions within the life sciences environment.
Qualifications:
MSc (PhD preferable) in computer science, statistics, computational biology or related fields advantageous
At least 5 years of experience in data science / business intelligence / statistics role supporting AI/ML projects in clinical research, pharmaceutical, CRO or medical device setting
Extensive programming experience in Python technology stack (pandas, numpy, scikit-learn, scikit-survival, matplotlib, seaborn, shap etc.) and experience in working with virtual environments and version control (e.g. git)
Excellent knowledge of machine learning algorithms for clustering, classification, regression, anomaly detection, and optimization, preferably with both small and big data
Experience in AI/ML applications in cardiology will be considered a plus
Exposure to cloud computing platforms, preferably AWS and Google Cloud
Excellent English language skills, storytelling and communications skills both oral and written, especially in explaining complex concepts in simple terms
Requirements:
Start: 05.10.2026
Duration: 12 months
Capacity: 5 days per week
Location: 100% remote
)