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Tier-1 brand, metro location, and broad AI/ML skillset increase applicant competition.
Core ML/GenAI skills transfer well, though pharma-specific data knowledge is moderately preferred.
Explicit 1–3 years, mandatory AI/ML projects and core tech skills create strict screening.
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Develop and deploy scalable AI/ML systems including AI copilots, NLP pipelines, and real-time decision engines to impact commercial and patient access strategies.
Collaborate with senior data scientists and engineers to transform AI prototypes (GenAI, LLM, ML) into production-ready platforms integrating structured and unstructured data.
Contribute to AI-driven automation and insights by building APIs, dashboards, and anomaly detection models supporting business decisions.
Bachelor's or master’s degree in Computer Science, AI, Data Science, Statistics, Engineering, or other STEM field.
1–3 years of hands-on experience in AI/ML, data science, or software engineering roles.
Proven experience with at least 2-3 real AI/ML projects including LLM-based chatbots with RAG or deployed ML models and data pipelines.
Strong programming skills in Python, PySpark, SQL; knowledge of ML techniques (Regression, Classification, Clustering); working knowledge of NLP fundamentals and LLM exposure.
Experienced in building production-grade AI/ML solutions involving LLMs, prompt engineering, and multi-modal data integration.
Comfortable turning complex business requirements into technical AI/ML specifications working in cross-functional global teams.
Familiar with MLOps, backend API development, scalable data engineering, and deployment in cloud or data analytics platforms.