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Generalist senior ML role, metro location, mid-level experience range, and broad skillset drive high competition.
Strong ML foundations are transferable, but pharma commercial analytics preference raises domain specificity to medium.
Explicit 4–10 years plus mandatory ML/AI stack and pharma analytics expertise increases filter strictness.
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Lead AI-driven analytics projects for Lifesciences/Pharma domains, focusing on Marketing, Sales, Medical, and Commercial Operations to deliver measurable business value.
Manage multiple projects independently and lead small teams to deliver quality AI/ML solutions including marketing mix modelling, promotion effectiveness, omnichannel analytics, and forecasting.
Develop AI/GenAI POCs, reusable code, scalable analytics frameworks, maintain knowledge assets, and engage with senior client stakeholders for recommendations and presentations.
Work Experience: 4–10 years in Advanced Analytics, Data Science or AI; 2–4 years preferred in Healthcare, Lifesciences, or Pharmaceutical Analytics.
Technical Skills: Proficiency in Python or PySpark for ML/statistical modeling, experience with Regression, Classification, Clustering, NLP, Generative AI, Deep Learning models, and Omnichannel Analytics.
Educational Qualification: B.Tech/Masters in Computer Science, Statistics, Applied Mathematics, Data Science, Bioinformatics, Operations Research, Econometrics, Economics or related quantitative discipline.
English language proficiency and experience working with global/cross-functional teams.
Experienced in delivering advanced AI/ML solutions specifically in pharmaceutical commercial analytics and Lifesciences domain.
Strong project management capabilities combined with technical expertise in state-of-the-art ML/DL and Generative AI methods.
Comfortable leading small teams and managing multiple projects with high client interaction and stakeholder communication.