Data Scientist

As a Data Scientist, your mission is to build and continuously improve machine-learning driven predictive models that help customers anticipate vacuum asset failures from day one.

This is an exciting opportunity to help us grow a high-impact Data Science Team within our Semiconductor Service division. The Semiconductor Service Division is a growing, global organisation focused on scaling service excellence and accelerating transformation through technology. You will report to the Principle Data Scientist and be part of a dynamic growing team to create customer value globally.

You will

• Build ML-based tooling that turns large training datasets into highly accurate, generic predictive models that can be applied on Day 1 of a customer engagement.
• Design and iterate model training processes, and help transition them into automated, production-grade pipelines (including retraining and re-tuning as new data arrives).
• Partner with Data Engineers, DevOps, and domain experts to shape datasets, features, evaluation approaches, and deployment patterns.
• Communicate insights and recommendations clearly to stakeholders, choosing the right medium for the audience (technical deep-dives, storytelling, dashboards, presentations).
• Participate in design sessions and code peer reviews, contributing to shared standards and best practices.
• Stay current with state-of-the-art data science methods and tooling, building internal/external peer networks to accelerate learning for yourself and the team.

You have 5+ years of experience, working as a Data Scientist (or in a closely related role) building machine-learning models from real-world data.

• Degree (or equivalent experience) in Computer Science, Engineering, Physical Sciences, or another mathematics-based discipline.
• Strong hands-on experience with mainstream analytics/programming languages (e.g., Python, R, MATLAB, Scala).
• Proven ability to develop, evaluate, and iterate predictive models using large datasets and sound statistical/ML methods.
• Comfortable building production-minded code: version control (e.g., Git/SVN), reproducibility, and collaborative development.
• Experience with cloud and scalable computing environments; containers and automated deployment are a plus.
• Excellent written and spoken English; additional European or Asian language skills are beneficial.