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Popular mid-level Data Scientist role in Bengaluru with broad GenAI requirements increases candidate competition.
GenAI skills are transferable but healthcare data, EHR standards, and regulatory knowledge impose moderate industry specificity.
Multiple explicit mandatory ML/LLM, cloud, MLOps, and evaluation requirements create rigid screening filters.
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Design, develop, and deploy ML, Gen AI, NLP, LLM models for AI data pipelines including RAG and prompt engineering.
Analyze large healthcare datasets to build statistical models for clinical decision support, patient risk stratification, and revenue cycle optimization.
Create automated data pipelines and deploy models on cloud platforms while collaborating with cross-functional teams to present data-driven insights.
Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or related quantitative field.
5-7 years of hands-on experience in data science, analytics, or machine learning roles.
Hands-on experience (at least 5 years) with pretrained language models (GPT, BERT, T5, Claude, Llama) including fine-tuning and prompt engineering.
Proficiency with cloud platforms (Azure, AWS, GCP), containerized deployments (Docker, Kubernetes), programming in Python or R, and experience with SQL and machine learning frameworks.
Experienced in building generative AI applications using frameworks like Hugging Face Transformers, Lang Chain, or OpenAI API, with strong prompt engineering skills.
Familiar with healthcare data, clinical standards (HL7 FHIR, ICD-10, CPT, SNOMED CT), and regulatory compliance including data privacy regulations (HIPAA, HITECH).
Able to evaluate AI models with advanced metrics and implement AI safety and alignment principles in multi-modal AI systems.