## [Scientific Computing Engineer - Drug Product Process Modeling & Data Science](/req-10087078-scientific-computing-engineer-drug-product-process-modeling-data-science "Scientific Computing Engineer - Drug Product Process Modeling & Data Science")
Job ID REQ-10087078
Sep 30, 2026
LOC_IN
### About the Role
Major Accountabilities
- Develop and apply mechanistic, empirical, statistical, and hybrid modeling approaches to support drug product formulation and process development, especially for process understanding, scale-up, and manufacturing-relevant questions.
- Translate formulation and process questions into model- and data-ready problem statements; define success criteria, assumptions, and uncertainty considerations with subject-matter experts.
- Apply statistics, Design of Experiments, multivariate analysis, and data-driven modeling to plan experiments, analyze results, and accelerate learning cycles.
- Build predictive models and decision-support tools for key drug product unit operations, with particular interest in oral solid dosage forms, powder technology, formulation, and process engineering.
- Build end-to-end data science solutions including 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 workflows for data preparation, modeling, analysis, and reporting, while maintaining scientific oversight and practical usability.
- Contribute to knowledge sharing, documentation, internal standards, and reusable modeling/AI assets within the global modeling and digital community.
Essential Skills
- Master’s degree or PhD in mechanical engineering, process engineering, chemical engineering, pharmaceutical engineering, materials science, applied mathematics, statistics, data science, or a closely related quantitative engineering discipline.
- Early-career profile preferred, typically with 2–4 years of relevant industry experience after a master’s degree or 0–4 years after a PhD, and a clear motivation for hands-on modeling, coding, and applied problem solving.
- Core skills
- Strong engineering and mathematical foundation, including process science, transport phenomena, statistics, numerical methods, and/or mechanistic modeling.
- Must have hands-on programming experience in Python or a similar programming language, with the ability and motivation to become productive in Python very quickly if not already fluent.
- Experience applying statistics, DoE, data analysis, simulation, optimization, and/or machine learning to engineering or scientific problems.
- 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 & standards.
- Strong communication skills to explain technical concepts to non-experts and influence decisions.
- Digital & AI capabilities (beneficial; can be developed on the job)
- Basic experience with machine learning, model evaluation, or AI-enabled analytics is an advantage, but less important than strong engineering fundamentals, coding ability, and learning agility.
- Interest in AI-assisted modeling, automation, and agent-based workflows, with willingness to learn and apply these methods in a scientifically rigorous way.
- Understanding of model lifecycle management, reproducibility, and deployment considerations in regulated environments.
- Experience with visualization and storytelling, such as dashboards or clear technical reporting.
Desirable Skills
- Experience or academic exposure to powder technology, formulation science, oral solid dosage forms, pharmaceutical unit operations, process modeling tools, PBM, DEM, gPROMS, or digital twins.
- Exposure to QbD principles, PAT concepts, or regulatory-relevant modeling activities.
- Experience working in global matrix organizations.
### Role Requirements
**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](https://www.novartis.com/about/strategy/people-and-culture "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)](https://www.novartis.com/sites/novartis_com/files/novartis-life-handbook.pdf)
Division DIV_GD
Business Unit Development
Location LOC_IN
Site Hyderabad (Office)
Company / Legal Entity IN10 (FCRS = IN010) Novartis Healthcare Private Limited
Functional Area FCT_DD
Job Type Full time
Employment Type Regular
Shift Work No
[Apply to Job](https://novartis.wd3.myworkdayjobs.com/en-US/Novartis_Careers/job/Hyderabad-Office/Specialist--Data-Science---Artificial-Intelligence_REQ-10087078 "Apply to Job")
Job ID REQ-10087078
### Scientific Computing Engineer - Drug Product Process Modeling & Data Science
[Apply to Job](https://novartis.wd3.myworkdayjobs.com/en-US/Novartis_Careers/job/Hyderabad-Office/Specialist--Data-Science---Artificial-Intelligence_REQ-10087078 "Apply to Job")