Principal AI Scientist (m/f/x)
Invenda GmbH
Contact person: Aleksandra Ivanova
München, Germany
Medicine and PharmaceuticalsBig DataComputational BiologyMachine LearningAzure Machine LearningData ScienceScikit LearnMachine Learning OperationsArtificial Intelligence Markup Language (AIML)
Description
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 complying with AI/ML standards and regulations, 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.
Requirements:
- 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 oncology (e.g. transcriptomics data, foundation models like scConcept) 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
Workload: 5 Days/Week
Remote Option: 100% Remote
Travel Requirements: None