Graduate Data Scientist - Supply Chain for Industrial Gases

BE01 Air Products SA/NV (BE); Diegem; On-site; EUR 50,000 - 65,000; Full time

Benefits offered by this job

Graduate program

Mentoring and coaching

International exposure

Job summary

Air Products is offering a role-ready graduate program in Industrial Gases Supply Chain Data Science in Europe. You will work in the Central Supply Chain Analysis Team on advanced analytics, ML, optimization, and visualization across multiple countries.

The program emphasizes hands-on projects, mentoring, and rapid responsibility, with opportunities to shape distribution networks and cost efficiency using Python, SQL, and modern data platforms.

Qualifications

• Master's degree in data science, computer science, math, statistics or related field.
• Strong programming skills in Python and SQL; solid ML/statistics knowledge.
• Ability to translate business problems into analytical models with rigor.

Responsibilities

• Explore and model large supply chain datasets to uncover patterns and opportunities.
• Design, train, and validate ML models such as forecasting and anomaly detection.
• Develop optimization and simulation models for network and transport planning.
• Turn models into deployable analytics products and dashboards with clear docs.
• Define KPIs and perform cost–benefit analyses for new models.
• Collaborate with data engineering, IT, and business teams across Europe.

Skills

Python

SQL

Statistics

Machine learning

Optimization

Geospatial analysis

Data visualization

English fluent

Education

Master's degree in Data Science

Tools

Pandas/NumPy

scikit-learn

Qlik Sense

Power BI

Databricks

Job description

Air Products is offering a role-ready graduate program in Industrial Gases Supply Chain Data Science in Europe. You will work in the Central Supply Chain Analysis Team on advanced analytics, ML, optimization, and visualization across multiple countries.

The program emphasizes hands-on projects, mentoring, and rapid responsibility, with opportunities to shape distribution networks and cost efficiency using Python, SQL, and modern data platforms.