Process Modeling Engineer – Customer Team

Process Modeling Engineer – Customer Team
Portalegre
Portalegre, Portalegre District, Portugal

About the Company

Data
How AG is a
- off company of ETH Zurich founded in 2017. Our mission is to bring Industry 4. 0 to the chemical, pharmaceutical, and biopharmaceutical sectors. We develop and commercialise predictive software that integrates sensor signals, process models, machine learning, reinforcement learning, historical data, and process engineering knowledge. Our technology accelerates process development, transfer, manufacturing, and risk & quality management—already trusted by 8 of the world’s 20 largest pharma companies.

About the Role

As a Process Modeling Engineer on our Customer Team, you will play a key role at the interface between
- edge process modeling and
- world industrial applications. The position combines technical depth with
- facing responsibilities and offers the opportunity to work closely with our international clients and multidisciplinary internal teams.

Responsibilities

Process Modeling & Data Analysis

• Conduct independent research and analysis using deterministic, statistical, and hybrid models for
  - series and dynamic process data.
• Collaborate with industrial partners to translate complex process challenges into actionable
  - based insights.

Modeling & Machine Learning Expertise

• Design, implement, and validate machine learning and statistical models tailored to bioprocess data, ensuring robustness, interpretability, and practical applicability.
• Integrate process engineering knowledge with
  - driven approaches to build hybrid
  - ML models.
• Work with numerical methods (e. g. , ODE solvers, optimization routines) and experiment with advanced approaches such as dynamic modeling, Bayesian methods, or reinforcement learning where applicable.
• Ensure reproducibility and maintainability of modeling workflows through clean coding practices, documentation, and version control (Git
  Lab).

Customer-Facing Activities

• Deliver process data analysis and modeling services to a diverse international client base through both Data
  How
  Lab and custom machine learning implementations.
• Participate in
  - functional teams—internally and on the client side—to support multidisciplinary
  - making.
• Communicate technical results and key insights clearly from scientific, operational, and business perspectives.

Training & Support

• Lead client training sessions on Data
  How
  Lab to ensure strong user adoption and effective usage.
• Provide ongoing technical support and guidance to clients.

Internal & Strategic Contributions

• Contribute to organizational, operational, and marketing initiatives that support the growth of our customer and user community.
• Examples include: visits to our Zurich headquarters, participation in our annual Data
  How Symposium, and contributions to internal knowledge sharing or customer success processes.

Qualifications

• Excellent university degree (Master’s or Ph
  D preferred) in computer science, (bio)informatics, (bio)statistics, chemical engineering, biotechnology, or related fields.
• Expertise in modeling of
  - series or dynamic process data.
• Solid coding experience in Python.
• Experience in data analytics and machine learning.
• Strong communication skills and enthusiasm for interacting with clients in a scientific/technical context.
• Ability to work effectively in
  - functional teams as well as independently.
• Fluency in written and spoken English.
• Motivation to work in a
  - moving, internationally active
  - up.

Required Skills

• Understanding of biopharmaceutical processes and unit operations (e. g. , cell culture, chromatography, filtration, virus inactivation).
• Experience with numerical solutions of ODE/PDE systems or optimization problems.
• Familiarity with Python data science tools (Num
  Py, Pandas, Py
  Torch,
  - learn, etc. ).
• Experience using Git
  Lab for project collaboration.

Pay range and compensation package

Integration into a young, dynamic, and interdisciplinary team of computationally driven chemical engineers, biotechnologists, and computer scientists. Hybrid work model, with flexibility between our main office in Lisbon and home office. A highly versatile role balancing advanced research,
- world industrial applications, and customer interaction. A steep learning curve, significant responsibility, and exposure to
- impact international projects. Opportunities for travel, conferences, and participation in
- wide community events. Attractive working conditions and clear opportunities for career progression.

Equal Opportunity Statement

Data
How AG is committed to diversity and inclusivity in the workplace. We encourage applications from individuals of all backgrounds and experiences.