Manager, Pharmaceutical Product Development GenAI & Data Science
Working with Us
Shape the Future of AI-Driven Pharmaceutical Product Development (PD)
What You Will Do
- Partner with senior scientific functional leaders and scientists across Chemical Process Development, Biologics Development, Drug Product Development, and Analytical Development to identify opportunities where AI and GenAI can create transformative business impact.
- Drive development of next-generation capabilities spanning GenAI, Agentic AI, Machine Learning, Knowledge Discovery, and Decision Intelligence.
- Establish best practices for critical thinking, problem framing, and AI-enabled decision making.
- Influence enterprise modelling strategy and investments across Product Development.
- Mentor data scientists and AI practitioners in the team and build a culture that balances technical excellence with curiosity, courage, and collaboration.
- Translate emerging GenAI capabilities into scalable products that generate measurable business outcomes and value.
What Makes You Successful
You understand that the most valuable skill in the era of AI is not model building, but problem framing, and critically probing problem statements, AI output, and assumptions. You should be comfortable with:
- Challenging assumptions before accepting requirements.
- Asking first-principles questions.
- Navigating ambiguity and shaping incomplete ideas into meaningful next steps through collaboration with PD functions.
- Building trust across technical and non-technical stakeholder groups.
- Communicating complex concepts with clarity and executive presence.
- Inspiring teams through influence rather than authority.
Qualifications
- Advanced degree in Data Science, Chemical Engineering, Applied Mathematics, or a related discipline.
- 7+ years of experience in Data Science, AI/ML, GenAI, and Digital Innovation.
- Demonstrated experience working in advanced innovation teams and influencing senior stakeholders.
- Deep expertise in Machine Learning, AI, GenAI with deep technical and hands on experience in the following areas:
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Artificial Intelligence & Machine Learning
- Statistics, Supervised & Unsupervised Learning, Bayesian Modelling, Probabilistic approaches, Cluster Analysis, Deep Learning, Time-Series Modelling, Causal Inference, Optimization
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Generative AI
- Large Language Models, Reasoning Models, Retrieval-Augmented Generation (RAG), Agentic Workflow Design, Multi-Agent Systems, Knowledge Graph Integration, LLM Evaluation Frameworks, Synthetic Data Generation, AI Safety & Guardrails, Human-in-the-Loop AI Systems
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Advanced Data Science Tools/Platforms
- PySpark, Python, TensorFlow, XGBoost, LightGBM, LangChain, LangGraph, MLflow
- AWS, Databricks, Hugging Face, CI/CD Pipelines, Feature Stores, Vector Databases, Model Serving Frameworks
- Strong track record of delivering business impact through data-driven solutions.
Preferred Experience
- Domain understanding of pharmaceutical product development and/or manufacturing domain.
- Agentic AI architectures.
- AI governance and responsible AI frameworks.
- Some prior exposure to hybrid mechanistic-AI approaches, physics informed ML
- Contributions to building and scaling data science organizations.
If you come across a role that intrigues you but doesn't perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career.
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