Process Engineering Intern: Data-Driven Improvements

Haleon; Nyon; On-site; CHF 20,000 - 25,000; Part time

Benefits offered by this job

25 days vacation

Flexible working

Pension plan

On-site fitness center

Corporate discounts

Subsidized restaurant/cantry

Training opportunities

Mobility support

Job summary

Haleon is recruiting a Process Engineer Intern for our Nyon site to join the Manufacturing or Packaging team. The role focuses on supporting OEE improvements, learning equipment processes, and driving data-driven optimization over a 6-month period.

We seek an engineering student with an interest in production systems and data analysis, capable of translating findings into practical recommendations while collaborating with multiple functions.

Qualifications

• Engineering student in Industrial/Mechanical/Manufacturing/Process Engineering or related field
• Interest in production systems and data analysis
• Able to structure problems and translate findings into practical recommendations
• Strong problem solving and communication skills
• Able to work with shop-floor teams and cross-functional stakeholders
• Able to interpret data and contribute to structured improvement work under supervision

Responsibilities

• Support OEE and process-improvement projects.
• Understand assigned equipment and processes.
• Define issues and analyze process data.
• Identify and evaluate improvement solutions.
• Support implementation with quality, engineering, R&D, maintenance, finance.
• Communicate progress and recommendations with stakeholders

Skills

Data analysis

Process optimization

Production systems

Problem solving

Education

Industrial/Mechanical/Manufacturing/Process Engineering student

Tools

Excel

Statistical analysis

Job description

Haleon is recruiting a Process Engineer Intern for our Nyon site to join the Manufacturing or Packaging team. The role focuses on supporting OEE improvements, learning equipment processes, and driving data-driven optimization over a 6-month period.

We seek an engineering student with an interest in production systems and data analysis, capable of translating findings into practical recommendations while collaborating with multiple functions.