At a Glance
- Tasks: Build and improve machine-learning models to predict vacuum asset failures.
- Company: Join a global leader in semiconductor services focused on innovation.
- Benefits: Enjoy a culture of trust, lifelong learning, and comprehensive benefits.
- Other info: Opportunity for career growth and collaboration with experts worldwide.
- Why this job: Make a real impact in a dynamic team while working remotely.
- Qualifications: 5+ years in data science with strong programming skills in Python or R.
The predicted salary is between 60000 - 80000 € per year.
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.
Responsibilities
- 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.
Qualifications
- 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.
Benefits
- Culture of trust and accountability
- Lifelong learning and career growth
- Innovation powered by people
- Comprehensive compensation and benefits
- Health and well-being
This role offers remote working with occasional travel required to our Global Technology Centre in Burgess Hill, United Kingdom (GB).
Data Scientist employer: Edwards Vacuum
As a leading player in the Semiconductor Service division, we pride ourselves on fostering a culture of trust and accountability, where innovation is driven by our talented team. With a strong emphasis on lifelong learning and career growth, we offer comprehensive benefits and the flexibility of remote working, complemented by opportunities to collaborate at our Global Technology Centre in Burgess Hill. Join us to be part of a dynamic environment that values diverse experiences and empowers you to make a meaningful impact from day one.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to current employees in the Semiconductor Service division on LinkedIn. A friendly chat can give you insider info and might just get your application noticed.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine-learning projects. Whether it's a GitHub repo or a personal website, let your work speak for itself and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for the interview by brushing up on your storytelling skills. Be ready to explain your past projects and how they relate to predictive modelling. Remember, it’s all about communicating insights clearly!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets into the right hands. Plus, we love seeing candidates who take that extra step.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the Data Scientist role. Highlight your experience with machine-learning models and any relevant projects you've worked on. We want to see how your skills align with our mission!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to tell us why you're passionate about data science and how you can contribute to our Semiconductor Service division. Keep it engaging and personal, so we get a sense of who you are.
Showcase Your Technical Skills:Don’t forget to mention your hands-on experience with programming languages like Python or R. If you've worked with cloud environments or automated deployment, let us know! We love seeing those technical chops in action.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates. Plus, it’s super easy!
How to prepare for a job interview at Edwards Vacuum
✨Know Your Models Inside Out
Make sure you can discuss the machine-learning models you've built in detail. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This shows your depth of knowledge and problem-solving skills.
✨Showcase Your Collaboration Skills
Since you'll be working with Data Engineers and DevOps, highlight any past experiences where you successfully collaborated with cross-functional teams. Share specific examples of how you contributed to shared goals and improved processes.
✨Prepare for Technical Deep-Dives
Expect to dive deep into technical discussions during the interview. Brush up on your programming languages like Python or R, and be prepared to discuss your experience with version control and production-grade code. Practice explaining complex concepts in simple terms.
✨Communicate Clearly and Confidently
Your ability to communicate insights is crucial. Prepare to present your past projects or findings in a clear and engaging way. Use storytelling techniques to make your points relatable, and tailor your communication style to your audience.
