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Strong employer brand and metro location increase competition, but niche GenAI-pharma specialization and seniority moderate applicant density.
Pharma product development domain expertise required, so candidates from other industries face high switching cost.
Mandatory 7+ years, advanced degree, deep GenAI/ML toolset and pharma domain make filters strict.
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Lead development and deployment of GenAI, AI/ML, and data science solutions targeting pharmaceutical product development and manufacturing challenges.
Collaborate with senior scientific leaders across multiple development domains to identify AI-driven impact opportunities and implement next-generation AI capabilities including Agentic AI and Decision Intelligence.
Mentor and guide AI/data science team members, establish best practices for problem framing and AI-based decision making, and influence enterprise modelling strategy.
Advanced degree in Data Science, Chemical Engineering, Applied Mathematics, or related field.
7+ years experience in Data Science, AI/ML, GenAI, and digital innovation.
Deep technical expertise and hands-on experience with AI/ML techniques including generative AI, large language models, time-series modeling, and AI tools like Python, TensorFlow, LangChain.
Work Experience Required: 7+ years; Notice Period: Not explicitly mentioned in the JD.
Experienced in partnering with senior scientific functional leaders and navigating ambiguous, cross-disciplinary pharma development projects.
Strong in problem framing and critical questioning rather than just model building; comfortable influencing through collaboration and clear communication with technical and non-technical stakeholders.
Domain familiarity with pharmaceutical product development or manufacturing and exposure to hybrid mechanistic-AI approaches or AI governance frameworks preferred.