Summary
You will work in a highly interdisciplinary environment, collaborating with formulation scientists, process engineers, data scientists, and manufacturing experts to advance model-informed decision-making and embed AI-native workflows into day-to-day development activities.
Rather than applying models in isolation, you will design AI-native workflows where mechanistic understanding, data-driven models, and human expertise work together.
About the Role
Major Accountabilities:
- You will combine process and product understanding with AI and advanced analytics to deliver decision support across the drug product lifecycle.
- The focus is on practical impact through AI-supported product development—modeling, experimentation, and knowledge management.· Apply mechanistic, empirical, statistical, and hybrid (physics + machine learning) modeling approaches to support drug product formulation and process development from early lab phase through scale-up and commercialization.· Translate formulation and process questions into model- and data-ready problem statements; define success criteria, assumptions, and uncertainty considerations with subject-matter experts.· Use AI and advanced analytics to guide experimentation (e.g., model-based Design of Experiments, Bayesian Optimization), accelerate learning cycles, and continuously refine models as new data becomes available.· Develop predictive models, digital twins, and decision-support tools for key drug product unit operations (e.g., oral solid dose manufacturing).· Build end-to-end data science solutions (data preparation, exploratory analysis, modeling, validation, deployment, and lifecycle management) with a focus on transparency and reproducibility.· Create clear visualizations, dashboards, and technical narratives to communicate insights and support decision making for diverse stakeholders.· Contribute to automation and AI-assisted/agent-based workflows for data preparation, modeling, analysis, and reporting - improving efficiency while maintaining scientific oversight.Contribute to knowledge sharing, documentation, internal standards, and reusable modeling/AI assets within the global modeling and digital community
Minimum Requirements
- Master’s degree or PhD in chemical engineering, pharmaceutical sciences, mechanical engineering, materials science, physics, applied mathematics, statistics, data science, or a related quantitative discipline.
- Experience or strong interest in pharmaceutical development and manufacturing processes or other complex process environments. Solid understanding of transport phenomena, process science, and/or statistical modeling principles.
- Hands-on experience with programming and data analysis (primarily Python; R is a plus).Experience applying statistics, DoE, multivariate analysis, and/or machine learning in scientific or industrial settings.
- Experience using or developing machine learning models (including model evaluation and validation).
- Familiarity with AI-assisted modeling, automation, and/or agent-based workflows. Understanding of model lifecycle management, reproducibility, and deployment considerations in regulated environments.
- Experience with visualization and storytelling (e.g., dashboards or clear technical reporting).
Desirable Requirements:
- Experience with pharmaceutical process modeling tools (e.g., PBM, gPROMS, DEM tools) and/or digital twins. Strong communication skills to explain technical concepts to non-experts and influence decisions.
- Exposure to Qods principles, PAT concepts, or regulatory-relevant modeling activities. Experience working in global matrix organizations. Ability to work with experimental and industrial datasets, including data cleaning, exploratory analysis, and uncertainty-aware interpretation including model credibility assessments according to regulatory guidelines & standard.
Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people-and-culture
Benefits and Rewards: Learn about all the ways we’ll help you thrive personally and professionally.
Read our handbook (PDF 30 MB)
Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve.
Accessibility and accommodation
Novartis is committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the recruitment process, or in order to perform the essential functions of a position, please send an e-mail to [email protected] and let us know the nature of your request and your contact information. Please include the job requisition number in your message.
