Applied Machine Learning & Process Modeling Engineer (Water Treatment)

This role sits at the intersection of process engineering, applied mathematics, and machine learning, with a strong focus on real-world industrial impact.

You will work closely with engineers and plant operators to:

• Improve operational efficiency

• Reduce cost and environmental footprint

• Increase understanding and robustness of our systems

How you'll make an impact:

• Develop predictive models for water treatment processes (e.g., ACF, IEX, RO)

  • Data-driven models (regression, tree-based methods, etc.)

  • Physics-informed or hybrid models

• Translate operational data into actionable insights

• Build simple, robust models that can be used by engineering and operations teams

• Analyze plant performance to identify optimization opportunities

• Work with multidisciplinary teams (process, automation, software)

• Support deployment of models into engineering tools or operational workflows

• Participate in on-site visits internationally to understand systems and validate models

Qualifications:

We are looking for a hands-on problem solver who can bridge theory and real-world systems.

Must-have:

• MSc or PhD in:

  • Applied Mathematics, Data Science, Chemical Engineering, Environmental Engineering, or similar

• 2+ years of experience

• Strong understanding of industrial water processes and field applications

• Good programming skills (Python preferred: pandas, NumPy, scikit-learn, etc.)

• Solid understanding of:

  • Modelling / simulation (deterministic or statistical)

  • Data analysis and signal interpretation

• Ability to work with noisy real-world data (not clean academic datasets)

• Fluent in English

Additional Qualifications:

• Experience with:

  • Water treatment or process industries

  • Time-series analysis, control systems, or optimization

  • First-principles modeling (mass balance, transport phenomena)

• Familiarity with:

  • Hybrid modeling (physics + ML)

  • Deployment of models into production tools

• Ability to communicate effectively with non-data specialists (operators, engineers)

What makes this role unique:

• Work on real industrial systems, not abstract datasets

• Direct impact on sustainability and water circularity

• Opportunity to shape the digital transformation of water treatment plants

• Combination of:

  • Field understanding

  • Engineering

  • Data science