Role Description

As a Data Scientist at mlHealth 360, you will lead our efforts in designing and developing advanced AI/ML models for medical imaging analysis. This role involves extensive R&D activities aimed at enhancing radiological diagnostics. Your work will directly contribute to enhancing medical imaging diagnostic accuracy, efficiency, and patient outcomes across a broad spectrum of healthcare challenges.

Key Responsibilities

• Architect and lead the development of AI models across diverse medical imaging domains.
• Collaborate with healthcare institutions for data acquisition and annotation.
• Evaluate and customize neural network architectures for medical image segmentation.
• Implement and refine machine learning algorithms for CT image analysis.
• Drive the iterative training and validation of models.
• Oversee the integration of models into clinical workflows and UI ecosystems.
• Lead the documentation and dissemination of research findings.

Required Skills and Qualifications:

• 5+ years of experience developing and deploying machine learning or deep learning models in enterprises.
• 3+ years of hands-on experience specifically in medical image analysis, preferably involving CT, MRI, or radiological workflows.
• Expertise in Python for data analysis and processing, image processing, segmentation techniques in medical imaging context.
• Proficiency in deep learning frameworks such as PyTorch, TensorFlow, or Keras.
• Excellent problem-solving, leadership, and communication skills.
• Knowledge of cloud computing platforms (AWS, Google Cloud, or Azure) for model training and deployment.
• Familiarity with version control systems (e.g., Git) and containerization technologies (Docker, Kubernetes) for code management and deployment.

Education:

• Master's or Ph.D. in Computer Science, Biomedical Engineering, Data Science, Medical Physics, or a related field.