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Mid-level ML role in Bangalore with generalist ML/GenAI skills and moderate company brand.
Requires healthcare-specific standards (FHIR, HEDIS, HIPAA), reducing cross-industry transferability.
Explicit 3–5 years, mandatory ML, FHIR and HIPAA compliance experience increases filter strictness.
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Build and maintain RAG pipelines, LLM prompt chains, and fine-tuned models for healthcare NLP abstraction.
Develop end-to-end ML pipelines handling healthcare datasets (eCQM, HEDIS, HCC risk adjustment) using FHIR-structured data, including feature engineering, deployment, and monitoring.
Collaborate cross-functionally to translate analytical requirements into scalable solutions and communicate insights via data visualizations to clinical and business stakeholders.
3 to 5 years of work experience in data science and machine learning roles.
Engineering degree required (BE/ME/BTech/MTech/BSc/MSc).
Proficiency in Python (ML/Data Science), SQL, Data Wrangling, and familiarity with healthcare data standards such as HL7 FHIR, eCQM, and HEDIS.
Basic experience with model evaluation, MLOps, and mandatory location requirement: Bangalore.
Experienced in healthcare data science applying ML to clinical datasets including EHR, claims, lab, and pharmacy data.
Strong knowledge of healthcare domain standards and compliance including HIPAA and model fairness/explainability requirements.
Capable of independently delivering production ML models with a focus on clinical NLP and data engineering pipelines in regulated healthcare environments.