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Data Science Lead

  • Hybrid
  • 6+ years

Salary

£70,000 - 85,000/ year

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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

Requirements

  • Experience leading or mentoring a team of data scientists, scientists or engineers
  • Hands-on data science in Python (NumPy, SciPy, pandas, scikit-learn or similar), turning exploratory work into quantified results
  • Heavy, day-to-day use of AI tools in your own technical work, such as coding assistants, LLMs and agentic workflows, with a critical eye for checking their outputs
  • Image processing, signal processing or statistical analysis of measurement data from scientific instruments
  • Statistical methods for measurement systems: uncertainty, repeatability, gauge R&R and drift
  • Machine learning and/or physics-based modelling, with the judgement to pick the right tool for the problem
  • Clear communication of results to technical and non-technical audiences, with evidence-based recommendations
  • Comfortable setting a roadmap and priorities, and knowing when a result is good enough to hand over
  • We’d love to see:
  • Atomic Force Microscopy or other nano-characterisation (SEM, FIB, profilometry), or semiconductor metrology and process control
  • Synthetic data generation or forward modelling of instruments
  • Building AI-assisted workflows or tooling for a team (agents, automated analysis pipelines, shared prompt libraries), and handing prototypes to software teams to productionise
  • A bit about us:
  • Our dynamic team of scientists and engineers is focussed on enabling the next generation of semiconductor devices through delivery of innovative products to customers around the world.
  • Our strength lies in the varied perspectives that come from different cultures, experiences, and identities. We believe that true innovation is fuelled by collaboration, locally and globally. We strive to foster an environment where everyone can contribute meaningfully and thrive. If you require adjustments to take part in the recruitment process, please let us know, we’ll do our best to support you.
  • Your recruitment journey:
  • We will interview you: Monday to Friday UK Time 9am to 4.30pm and we'll be as flexible as we can with Global Scheduling
  • 1st stage: (45 minute) Remote meeting to evaluate your experience and technical ability
  • 2nd stage: (2.5 hours) Face to face onsite evaluating technical, presentation and communication skills along with your ways of working and your opportunity to to know more about us
  • If you're not comfortable with eye contact, let us know at the start of your interview and if REMOTE, once we've said hello, feel free to turn your camera off until the end.
  • We dress casually so informal attire is absolutely fine for onsite interviews. We want you to feel comfortable when you meet us and if there's anything else we can do to support your journey, just let us know.
  • A note on how we use AI:
  • We use AI only to transcribe our interviews so we can focus fully on you instead of scribbling notes. The AI does not take part in any decision making at any stage. All hiring decisions are made by real humans based on the conversation we have with you.

Conditions

We recognise the value of flexibility and offer a hybrid working model wherever possible. Most employees work onsite three days per week, although some positions require a greater onsite presence due to the nature of the work and business need

Recruitment agencies: the company Ltd only works with approved agencies and does not accept unsolicited agency CVs. Please do not submit candidate details in response to this advert or solicit any the company Ltd employees. The company Ltd is not responsible for any fees related to unsolicited CVs.

Where you’d work

Hybrid, 3 days a week in the office

You can work from

  • United Kingdom

About the company

Company hidden

Office in United Kingdom

Your chances

Still hiring, not crowded yet, and you'd be among the first.

  • 17 checks run
  • 6 good signs
  • 0 red flags

Still hiring?

11 checks

Actively hiring

In its favour3

  • Still on the company's own careers site, checked 1 h agoModerate evidence
  • Found in the last 48 hours, before the big job boardsModerate evidence
  • A tight salary range, set for one seat: £70K to £85KSlight evidence

How crowded?

6 checks

Low

In its favour3

  • In its Early Window: not on the big job boards yetStrong evidence
  • Lead level: far fewer people qualifySlight evidence
  • Asks for scikit-learn, which fewer than 1% of open roles doSlight evidence

Fits Me

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  • Must-haves
Details12 facts · Role, Location, Compensation
Tech stack
  • Python
  • LLMs
  • scikit-learn
Seniority
Lead
Specialty
Data Science
Region
United Kingdom
Pay period
Annual
Show 7 more factsShow less

Role

Category
Data & Analytics
Specialty
Data Science
Seniority
Lead
Experience
6+ years
Tech stack
  • Python
  • LLMs
  • scikit-learn

Location

Work model
Hybrid
Region
United Kingdom
Office
  • United Kingdom
Remote from
  • United Kingdom
Days in the office
3 days

Compensation

Salary
£70,000 - 85,000 / year
Pay period
Annual

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