Data Scientist

As a GenAI Data Scientist at our company, you will be responsible for utilizing your expertise in medical imaging, radiology workflows, and service-oriented healthcare platforms to design, train, and deploy Generative AI and Agentic AI solutions. Your role will involve improving clinical efficiency, operational intelligence, reporting automation, and service optimization within healthcare systems. You will collaborate closely with product managers, clinical subject matter experts, engineering teams, and cloud architects to develop scalable AI-driven solutions for healthcare problems. Key Responsibilities: - Develop Generative AI & ML solutions for radiology reporting automation, imaging analytics, clinical decision support, and operational intelligence. - Create agentic AI workflows for tasks like study triage, report quality checks, and workflow optimization. - Fine-tune and evaluate LLMs and vision-language models using medical datasets. - Work with DICOM, non-DICOM, and multimodal data for medical imaging applications. - Collaborate with clinical experts to ensure the clinical relevance, safety, and interpretability of AI outputs. - Build data pipelines for ingesting data from healthcare platforms and implement model evaluation, monitoring, and continuous learning pipelines. - Apply AI to non-clinical service use cases like TAT optimization, resource utilization, and revenue leakage. - Deploy AI models as APIs and microservices, following MLOps best practices and cloud-native deployments. - Ensure compliance with HIPAA, GDPR, and healthcare data privacy standards, and implement explainability and bias mitigation in AI models. Required Qualifications: Education: - Bachelors or Masters degree in Computer Science, Data Science, AI/ML, Biomedical Engineering, or related field. Technical Skills: - Strong experience with Python and ML frameworks (PyTorch, TensorFlow, Hugging Face). - Hands-on experience with LLMs, prompt engineering, RAG, vector databases, and agent frameworks. - Knowledge of medical imaging standards (DICOM, HL7, FHIR preferred). - Experience with SQL/NoSQL databases, data lakes, and cloud platforms. Domain Knowledge: - Understanding of radiology workflows and enterprise imaging ecosystems. - Experience working with clinical, operational, or healthcare service data. Preferred Qualifications: - Experience building AI products for healthcare SaaS platforms. - Exposure to computer vision in medical imaging. - Knowledge of FHIR-based APIs and interoperability standards. - Experience with regulatory documentation and AI validation in healthcare. - Prior experience working with clinicians or hospital IT teams. Soft Skills: - Strong problem-solving and analytical mindset. - Ability to communicate complex AI concepts to non-technical stakeholders. - Comfortable working in fast-paced, cross-functional product teams. - Strong ownership and bias toward execution. As a GenAI Data Scientist at our company, you will be responsible for utilizing your expertise in medical imaging, radiology workflows, and service-oriented healthcare platforms to design, train, and deploy Generative AI and Agentic AI solutions. Your role will involve improving clinical efficiency, operational intelligence, reporting automation, and service optimization within healthcare systems. You will collaborate closely with product managers, clinical subject matter experts, engineering teams, and cloud architects to develop scalable AI-driven solutions for healthcare problems. Key Responsibilities: - Develop Generative AI & ML solutions for radiology reporting automation, imaging analytics, clinical decision support, and operational intelligence. - Create agentic AI workflows for tasks like study triage, report quality checks, and workflow optimization. - Fine-tune and evaluate LLMs and vision-language models using medical datasets. - Work with DICOM, non-DICOM, and multimodal data for medical imaging applications. - Collaborate with clinical experts to ensure the clinical relevance, safety, and interpretability of AI outputs. - Build data pipelines for ingesting data from healthcare platforms and implement model evaluation, monitoring, and continuous learning pipelines. - Apply AI to non-clinical service use cases like TAT optimization, resource utilization, and revenue leakage. - Deploy AI models as APIs and microservices, following MLOps best practices and cloud-native deployments. - Ensure compliance with HIPAA, GDPR, and healthcare data privacy standards, and implement explainability and bias mitigation in AI models. Required Qualifications: Education: - Bachelors or Masters degree in Computer Science, Data Science, AI/ML, Biomedical Engineering, or related field. Technical Skills: - Strong experience with Python and ML frameworks (PyTorch, TensorFlow, Hugging Face). - Hands-on experience with LLMs, prompt engineering, RAG, vector databases, and agent frameworks. - Knowledge of medical imaging standards (DICOM, HL7, FHI