Description
Data Science Lead | Semiconductor Metrology
Abingdon, UK
Reward and Benefits
£70,000 - £85,000 (depending on experience)
Annual bonus, 3x salary death in service benefit and private health care BUPA, EMI Share scheme.
If you are a Data Science Lead who enjoys turning measurement data into proof of what is possible, why not join us in Abingdon, Oxfordshire, and build and lead the Data Science team behind advanced semiconductor metrology systems.
We are looking for an ambitious and adaptable Data Science Lead to set up a new Data Science team in our Technology department, reporting to the Technology Director. You will lead a small team, initially a Data Scientist and a Modelling Scientist, and stay hands-on as a working lead data scientist. You will explore and prove new analysis methods, from synthetic data and information-limit studies to modelling, machine learning and AI, to improve the performance of our Metron3D systems and draw more insight from our data.
You will work hand in hand with the Data Analysis team in Engineering: you prove what is possible, they make it robust and shippable. You will also collaborate with R&D, System Design Engineering and Applications Development. We are an AI-first team, and you will set the standard for using AI tools well and safely. If your passion is speed, evidence and finding out what the data can really tell you, we’d love to hear from you.
What you’ll be doing
Lead, develop and mentor the Data Science team while staying hands-on, setting priorities and keeping a fast, evidence-based working rhythm
Own and deliver the Data Science roadmap: synthetic data, modelling, information-limit studies, algorithm development and data analysis tools
Establish the information limit, meaning what is physically extractable given instrument noise, limitations and tip geometry, and use it as the benchmark for every new method
Explore, test and benchmark new algorithms (for example PCA, percentile methods and machine learning) on real and synthetic data, covering achievable performance, measurement uncertainty and gauge capability
Define the handover to Data Analysis in Engineering (prototype code, test data, acceptance criteria and expected performance), and manage the demo and performance data libraries with Applications Development
Use AI tools every day, set the team’s standards for using them well and safely, and track the state of the art in third-party and open-source methods
Education and experience
MSc or PhD in Physics, Data Science, Applied Mathematics, Engineering or a similar subject, or [8] years’ relevant experience in data science or quantitative research, including some team leadership