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Tier-1 pharma, mid-level data/ML role in Bangalore with broad skills attracts many qualified applicants.
Strong pharma data, Veeva/IQVIA expectations and HIPAA/regulated compliance create high domain-specific fit sensitivity.
Multiple mandatory years, domain-specific MLOps/Snowflake/Cortex skills and compliance requirements increase filter strictness.
Develop, maintain, and deploy machine learning model pipelines from experimentation to production on Snowflake and Cortex AI platforms for rare disease commercial analytics.
Design and operate batch and streaming data workflows integrating diverse healthcare and commercial data sources to support AI/ML initiatives.
Build and manage autonomous agentic AI workflows that detect anomalies, generate insights, and recommend commercial actions while ensuring governance, compliance, and cost optimization.
3–6+ years experience in MLOps, Data Engineering, or ML platform roles including 2+ years building complex analytics or data science solutions.
Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field, or equivalent experience.
Proficiency in Python and SQL; experience with CI/CD pipelines, containerization (Docker), and cloud infrastructure.
Experience working onsite in Bengaluru, India; no notice period explicitly mentioned in the JD.
Strong hands-on expertise with Snowflake, Cortex AI, ML model lifecycle management, and AI agent system design within regulated healthcare environments.
Experience integrating and processing specialty pharma and commercial data for rare diseases, with knowledge of compliance frameworks such as HIPAA and FDA regulations.
Proven ability to build scalable, auditable, and compliant AI/ML production systems collaborating closely with data science, commercial analytics, and IT operations.