Advanced Process Modeling Expert

About the Role

As the Advanced Process Control Engineer, you will be responsible for driving control strategy initiatives by developing and deploying advanced process models, leveraging digital platforms and data infrastructure to enhance unit-operation analytics for forecasting, soft-sensing, and simulation. You will manage the lifecycle of these models, support data readiness for process simulation, and contribute to visualization and predictive modeling to optimize manufacturing processes and ensure high product quality.

Your Accountabilities
- Lead the execution of control strategy initiatives by implementing advanced process models tailored to product-specific, manufacturing unit operations. Develop and leverage digitizable, numerical models (mechanistic, hybrid, and statistical/machine learning) for soft-sensing, forecasting, and simulation, incorporating physical parameters and core principles such as thermodynamics, transport phenomena, fluid dynamics, and molecular kinetics.
- Own the lifecycle management of process models, ensuring their ongoing optimization, relevance, and alignment with operational and strategic objectives.
- Facilitate data readiness for process simulation (dry lab) to support process visualization, troubleshooting, problem-solving, and predictive modeling capabilities.
- Execute optimization initiatives to improve manufacturing efficiency, such as reducing process deviations, failure/discard rates, enhancing yield, and increasing productivity, while maintaining high product quality.
- Utilize NorthStar technologies and platforms to monitor manufacturing parameters and create product-specific AI solutions that support predictive process simulations and problem-solving capabilities.
- Design and document data blueprints, ensuring data availability, quality, and context are automated in the cloud, enabling the creation of scalable, ready-to-deploy process models, increasing automation, and preparing the factory of the future for manufacturing sciences.
- Collaborate on data contextualization and collection of end-user requirements to digitize manufacturing unit operations effectively.

What You Bring to Takeda
- Bachelor’s degree in a STEM field (Science, Technology, Engineering, or Mathematics - ideally Chemical/Biochemical Engineering); post-graduate degree (Master’s/PhD) is highly desirable.
- At least 3 years of experience in the pharmaceutical/biotech industry with familiarity in cGMP requirements.
- Proven expertise in digitizing industrial processes, computational modeling, process simulation, soft-sensor development, and data analytics.
- Advanced proficiency in statistical, machine learning, and AI methodologies.
- Expertise in mechanistic and hybrid modeling techniques, with experience using flow-sheeting software (e.g., gPROMS).
- Familiarity with Discoverant, SIMCA Online & Offline, OSI PI, Databricks, AWS Cloud Services is advantageous.
- Experience in developing soft sensors for drug manufacturing processes is a strong asset.
- Strong programming skills in Python, with additional expertise in R, Matlab, Plotly, Streamlit, RShiny, PowerBI, SQL, etc., considered a plus.
- Familiarity with project management methodologies, including SCRUM, is a strong advantage.
- Exceptional communication skills, with the ability to translate complex technical concepts into clear, understandable narratives for non-experts.
- Creative and forward-thinking, with a passion for leveraging cutting-edge technologies and methodologies to drive industrial process digital transformation.
- Fluent in English.

As an experienced professional, you specialize in solving various complex problems, sometimes referring to established precedents and policies. Your work involves analyzing diverse data and selecting appropriate methods for solutions, while networking with senior professionals in your field. You possess a complete understanding of principles, concepts, and industry practices, exerting some influence on organizational objectives. You often work independently under general direction, occasionally leading small project teams, and may represent the organization in contractual or project matters, interacting with senior internal and external personnel. You might also participate in training junior staff.

**Locations**: Zurich, Switzerland

**Worker Type**: Employee

**Worker Sub-Type**: Regular

**Time Type**: Full time