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- 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
Job location
This role offers remote working with occasional travel required to our Global Technology Centre in Burgess Hill, United Kingdom (GB).
Data Scientist in Burgess Hill employer: Edwards Vacuum
Contact Detail:
Edwards Vacuum Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in Burgess Hill
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or at industry events. Ask them about their experiences and the company culture. This can give you insider info and might even lead to a referral!
✨Tip Number 2
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in data science. Practice explaining complex concepts in simple terms, as you'll need to communicate insights clearly to stakeholders.
✨Tip Number 3
Showcase your projects! Create a portfolio of your machine-learning models and predictive analytics work. This not only demonstrates your skills but also gives you something tangible to discuss during interviews.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team.
We think you need these skills to ace Data Scientist in Burgess Hill
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! Share your passion for data science and how you can contribute to our Semiconductor Service division. Don’t forget to mention why you’re excited about this opportunity at StudySmarter.
Showcase Your Technical Skills: We love seeing hands-on experience! Be sure to include specific programming languages and tools you’ve used, like Python or R. Mention any cloud computing experience too, as it’s a big plus for us.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
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 collaborated with cross-functional teams. Share specific examples of how you contributed to shaping datasets or deployment patterns, as this will demonstrate your teamwork abilities.
✨Communicate Like a Pro
Prepare to present your insights clearly and effectively. Whether it's through storytelling or technical presentations, practice explaining complex concepts in simple terms. Tailor your communication style to your audience, as this is crucial for stakeholder engagement.
✨Stay Updated on Trends
Familiarise yourself with the latest data science methods and tools. Mention any recent trends or technologies you've explored during the interview. This shows your commitment to lifelong learning and your ability to bring fresh ideas to the team.