Senior Data Scientist

Job Title

Senior Data Scientist – Medical Imaging & Computer Vision (3–6 Years Experience)

Location

On-site Bengaluru

About Us

At nFerence Labs, the "Google of Biomedicine" (see also nference.ai/news for more information on our research work, including work related to Covid-19), we are building the world’s first massive-scale platform for pharmaco-biomedical computing. Our platform leverages AI and deep learning across clinical text, medical images, and other biomedical signals combined with large-scale high-performance computing to help pharmaceutical companies accelerate drug discovery and enable early diagnosis of critical diseases. We collaborate closely with premier medical institutions such as the Mayo Clinic to extract deep insights from patient data including clinical notes, lab information, medical images, ECG signals, and more. Our team is a unique blend of computer scientists, engineers, and domain experts including MDs and PhDs from institutions such as MIT, Harvard, the IITs, IISc, and other leading universities.

About The Role

We are seeking a Senior Data Scientist with strong expertise in medical imaging and computer vision to design, develop, and deploy advanced image analysis systems for healthcare applications. In this role, you will lead the development of AI models for medical image understanding including object detection, OCR, entity detection, and automated de-identification. You will work closely with clinicians, researchers, and engineering teams to translate clinical requirements into scalable AI solutions and contribute to building robust systems that directly impact healthcare diagnostics and research.

Key Responsibilities

• Design, develop, and deploy advanced computer vision models for medical imaging tasks such as disease detection, classification, segmentation, and anomaly detection.
• Develop and implement entity detection and automated de-identification pipelines to remove sensitive patient information from medical images.
• Build and optimize object detection and OCR systems for extracting structured information from medical imaging datasets.
• Work with medical imaging standards such as DICOM, PACS systems, and large-scale clinical datasets for model training, validation, and deployment.
• Build and maintain scalable model training and deployment pipelines using Docker and modern MLOps practices.
• Collaborate with radiologists, clinicians, data scientists, and engineers to translate clinical challenges into practical AI solutions.
• Perform data preprocessing, augmentation, and annotation to improve dataset quality and model performance.
• Conduct model evaluation, error analysis, and performance optimization to meet stringent clinical accuracy requirements.
• Research and implement state-of-the-art algorithms in medical image analysis and deep learning.
• Mentor junior team members and contribute to best practices in model development, experimentation, and documentation.
  
  

Required Skills And Qualifications

• 3–5 years of industry experience in computer vision, deep learning, or medical imaging.
• Bachelor’s or Master’s degree (PhD preferred) in Computer Science, Biomedical Engineering, Electrical Engineering, or a related field.
• Strong experience in medical image analysis, computer vision, and deep learning techniques.
• Hands-on expertise with frameworks such as TensorFlow, PyTorch, and OpenCV.
• Proven experience building object detection and OCR systems for real-world applications.
• Strong programming skills in Python with working knowledge of C++.
• Experience with Docker containerization, Git version control, and cloud platforms such as AWS, GCP, or Azure.
• Understanding of healthcare data privacy regulations such as HIPAA and responsible AI practices in healthcare.
• Strong analytical thinking, problem-solving ability, and attention to detail.
  
  

Preferred Skills

• Experience working with medical imaging datasets and healthcare AI systems.
• Knowledge of MLOps practices and model lifecycle management.
• Experience with model optimization tools such as TensorRT or ONNX.
• Familiarity with edge deployment or real-time inference systems.
• Experience collaborating with clinical or biomedical research teams.
  
  

What We Offer

• Opportunity to work on cutting-edge healthcare AI projects impacting real-world patient care.
• Collaborative environment with experts in AI, medical imaging, and clinical research.
• Flexible working hours and hybrid opportunities.
• Competitive salary and comprehensive benefits package.
• Access to high-end computing infrastructure and curated medical datasets.