DxD Hub is seeking an experienced Data Scientist to support new diagnostics product development and support data analytics in software development for Software as a Medical Devices. In this role, you will play a crucial role in driving the successful execution of diagnostic products in collaboration with external partners. The ideal candidate should possess a strong background in data science and Machine learning and deep learning is highly preferred.

Role & Responsibilities:

• Analyze healthcare related data for diagnostic applications; define problems, hypotheses, and analysis plans.
• Develop and optimize algorithms for data analysis, synthesis, visual recognition, object detection, segmentation, and signal pattern recognition etc.
• Design, execute, and document experiments to validate model assumptions and performance in line with regulatory requirements.
• Conduct feasibility studies and support clinical/analytical validation of AI-based algorithms for diagnostic use.
• Explore and integrate cutting-edge technologies into diagnostic AI solutions, ensuring robustness, reproducibility, and compliance.
• Translate business and clinical needs into data science projects, aligned with regulatory and quality management requirements.
• Collaborate with cross-functional teams (R&D, QA/RA, clinical affairs) to ensure AI models meet regulatory standards. (FDA, CE-IVDR, HSA, etc.).
• Prepare and maintain technical documentation, including design history files (DHF), risk assessments, software development lifecycle (SDLC) deliverables, and regulatory submissions.
• Support model deployment under SaMD frameworks, including monitoring, version control, and post-market surveillance.
• Stay current with trends in AI for diagnostics, SaMD regulatory guidance, and international standards.

Requirements:

• PhD or Master's degree in a quantitative field (Biomedical Engineering, Mathematics, Statistics, Computer Science, Physics, or related).
• 1-3 years of relevant working experience in AI development.
• Solid background in computer vision, deep learning, and image/signal data analysis algorithms, LLM etc.
• Hands-on experience with Python and major deep learning frameworks (TensorFlow, PyTorch, Keras etc.) and LLM.
• Strong communication skills to explain technical insights to both technical and non-technical stakeholders.
• Ability to work independently within a regulated development environment.
• Model performance evaluation, deployment and lifecycle management experience (MLOps, monitoring, data drift management).