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- Tasks: Develop and maintain statistical and machine-learning models for advanced manufacturing processes.
- Company: Join a collaborative Innovation Services team at a cutting-edge R&D facility.
- Benefits: Gain exposure to real-world engineering challenges and enhance your skills.
- Why this job: Make a tangible impact on production reliability and quality in a high-tech environment.
- Qualifications: Degree in STEM, strong programming skills, and analytical thinking required.
- Other info: Opportunities for career growth and collaboration with diverse teams.
The predicted salary is between 30000 - 50000 £ per year.
Your new role as a Data & Statistical Modelling Engineer involves joining a highly collaborative Innovation Services team, developing statistical and machine-learning models to understand and predict variation in advanced manufacturing processes. You will work closely with process, materials, and software engineers to identify and control key variables critical to scaling production across a growing fleet of additive manufacturing machines. Your work will directly influence production reliability, quality, and performance.
Key responsibilities include:
- Developing and maintaining statistical and ML models to analyse machine and material performance data
- Building and refining data pipelines to post-process experimental and operational data
- Collecting experimental data and owning frameworks that track performance over time
- Collaborating with testing engineers to design robust experiments and ensure high-quality training data
- Working with software engineers to embed modelling outputs into internal tools and platforms
- Communicating insights clearly to ensure your work delivers tangible value across the business
This role is based at a dedicated R&D facility and offers exposure to real-world, high-impact engineering challenges.
What you’ll need to succeed:
You will have a strong analytical background and enjoy applying data, statistics, and modelling techniques to complex physical systems. You will be comfortable working across disciplines and translating technical insight into practical outcomes.
Essential experience includes:
- A degree in Mathematics, Physics, Engineering, Computer Science, Data Science or a related STEM discipline (or equivalent experience)
- Strong programming skills, particularly in Python
- Excellent problem-solving and analytical thinking
- High attention to detail with the ability to manage work independently
- Strong communication skills and confidence working in cross-functional teams
Desirable experience includes:
- Industry or postgraduate experience in machine learning and/or statistical modelling
- Probabilistic programming and time-series forecasting
- Experience within additive manufacturing, particularly Laser Powder Bed Fusion
- Investigating and reducing variation in production or manufacturing environments
- Interest in high-performance applications such as aerospace, precision engineering or advanced electronics
If you’re interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now. If this job isn’t quite right for you, but you are looking for a new position, please contact us for a confidential discussion about your career.
Data and Statistical Modelling Engineer in Abingdon employer: Hays
Contact Detail:
Hays Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data and Statistical Modelling Engineer in Abingdon
✨Tip Number 1
Network like a pro! Reach out to professionals in the field of data and statistical modelling. Attend industry events, webinars, or even local meetups. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning and statistical models. This will give potential employers a taste of what you can do and how you approach complex problems.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with Python and any relevant projects. Practice explaining your thought process clearly, as communication is key in cross-functional teams.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search. So, hit that 'apply now' button and let’s get you started on this exciting journey!
We think you need these skills to ace Data and Statistical Modelling Engineer in Abingdon
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your analytical skills and experience in data and statistical modelling. We want to see how your background aligns with the role, so don’t be shy about showcasing relevant projects or coursework!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the Data & Statistical Modelling Engineer role and how your skills can contribute to our Innovation Services team. Keep it engaging and personal!
Showcase Your Programming Skills: Since strong programming skills, especially in Python, are essential for this role, make sure to mention any relevant projects or experiences where you've used these skills. We love seeing practical applications of your knowledge!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team!
How to prepare for a job interview at Hays
✨Know Your Models Inside Out
Make sure you can discuss the statistical and machine-learning models you've worked on in detail. Be prepared to explain how they apply to real-world scenarios, especially in manufacturing processes. This shows your depth of knowledge and ability to translate theory into practice.
✨Brush Up on Python Skills
Since strong programming skills in Python are essential for this role, ensure you're comfortable discussing your coding experience. Bring examples of projects where you've built data pipelines or implemented models, and be ready to tackle any technical questions that may come up.
✨Collaborate and Communicate
Highlight your experience working in cross-functional teams. Prepare examples of how you've collaborated with engineers from different disciplines, and think about how you can clearly communicate complex insights to non-technical stakeholders. This will demonstrate your ability to add value across the business.
✨Show Your Problem-Solving Skills
Be ready to discuss specific challenges you've faced in previous roles and how you approached solving them. Use the STAR method (Situation, Task, Action, Result) to structure your answers, focusing on your analytical thinking and attention to detail.
