At a Glance
- Tasks: Join a dynamic team to analyse data and develop machine learning solutions.
- Company: QinetiQ, a leader in data science and engineering with an inclusive culture.
- Benefits: Access to on-demand learning, coaching, 25 days holiday, and employee discounts.
- Other info: Flexible working environment with opportunities for career growth and collaboration.
- Why this job: Gain hands-on experience in data science while making a real-world impact.
- Qualifications: Studying Computing, Data Science, Mathematics, or Physics; Python and machine learning experience preferred.
The predicted salary is between 20000 - 30000 € per year.
At QinetiQ we are creating a workplace that is inclusive; where our differences are not only embraced but make us stronger. A place where we can connect with each other and benefit from the experiences and thinking from people with varied backgrounds, and at different stages in their careers.
About the team
Data Science & Engineering: Our role is to ensure our customers gain the maximum advantage from their data. We are involved at all stages of the data lifecycle from the initial gathering & processing stage, through the analysis phase, leading to actionable outputs & advice.
The Data Science and Engineering teams within Software Engineering, Communication Networks & Data Science (SECNDS) discipline consist of a mix of data scientists (exploring data sets and algorithms) and data engineers (building the infrastructure to capture and process the data). The team's skills however are varied and cover a wide range of disciplines. Our daily work involves applying both conventional and novel machine learning techniques to customer problems as appropriate to advise on and/or demonstrate the opportunities created through exploiting their data.
We have a strong pedigree in sensor design, data analysis & processing, and data fusion. We are at the cutting edge for designing tools, software and automation techniques that enable the rapid and timely transfer of relevant data and information. We also deal in information exploitation techniques, for real-world use but also in the fields of simulation and the design of synthetic environments. We develop and use numerical and mathematical models for a wide range of engineering and business applications.
What will I be doing?
The team works across all data types, everything from numerical data to natural language processing and signals analysis through to imagery interpretation. Where necessary, we also collect or simulate data using mathematical models.
A typical day will see you working as part of a small project team attending project meetings, preparing data, and applying the relevant Machine Learning or Artificial Intelligence techniques. You will be expected to code up solutions to support this work, and to integrate with the team's coding best practices. You may occasionally be involved in stakeholder engagements or presentations, and you will often help with the report writing process. Your days can have a mixture of on-site and home working, depending on the specific project's data requirements.
We frequently collaborate with colleagues and subject experts across the business to gain cross-domain insight to support our work.
Academic requirements
- Computing / Data Science
- Mathematics
- Physics
Additional requirements
- Good understanding of statistics (statistical analysis) is beneficial
- Experience in Python, cloud computing &/or machine learning is an advantage
- Practical experience (including hobbies & academic projects) of analysis data / AI / Machine learning / neural networks / cloud technologies is beneficial
Our Benefits (the list is not exhaustive)
- On demand learning, access to courses, modules, and lectures via multiple digital learning platforms
- Coaching and Mentoring
- 25 days annual holiday excluding bank holiday
- Matched contribution pension scheme, with life assurance
- Employee discount portal
- Employee Assistance Programme
- Employee-led networks
Security
Many of our roles at QinetiQ are subject to national security vetting. Applicants who already hold the appropriate level of vetting may be able to transfer it upon appointment, subject to approval. Many roles are also subject to restrictions on access to information, which means factors such as nationality, previous nationalities held and the country in which you were born may impact your role.
Please note that all applicants for this role must be eligible for SC clearance, as a minimum. Further guidance regarding clearances can be found: UKSV National Security Vetting Solution: guidance for applicants - GOV.UK (www.gov.uk)
Please also be aware that under immigration rules, our Early Careers roles do not meet the legal threshold for candidates who are resident in the UK on student visas.
Closing date for new applicants: 22nd May 2026
Data Scientist Year in Industry Placement- Farnborough or Malvern in Great Malvern employer: QINETIQ LIMITED
At QinetiQ, we pride ourselves on fostering an inclusive work environment that values diverse perspectives and experiences, making us a standout employer for aspiring data scientists. Our commitment to employee growth is evident through our extensive learning opportunities, coaching, and mentoring, alongside a collaborative culture that encourages innovation and teamwork. Located in the vibrant areas of Farnborough and Malvern, you will benefit from a dynamic workplace that not only supports your professional development but also offers a range of employee benefits, including a matched pension scheme and generous holiday allowance.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist Year in Industry Placement- Farnborough or Malvern in Great Malvern
✨Tip Number 1
Network like a pro! Reach out to current or former employees at QinetiQ on LinkedIn. Ask them about their experiences and any tips they might have for landing the Data Scientist placement. Personal connections can make a huge difference!
✨Tip Number 2
Prepare for interviews by brushing up on your technical skills. Make sure you can confidently discuss machine learning techniques and Python coding. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨Tip Number 3
Showcase your projects! If you've worked on any data analysis or machine learning projects, be ready to discuss them in detail. We love seeing practical experience, so highlight what you've done and the impact it had.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining the QinetiQ team. Good luck!
We think you need these skills to ace Data Scientist Year in Industry Placement- Farnborough or Malvern in Great Malvern
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that are relevant to the Data Scientist role. Highlight any projects or coursework related to data science, machine learning, or programming in Python. We want to see how you can contribute to our team!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how your background aligns with our mission at QinetiQ. Be sure to mention any specific experiences that demonstrate your analytical skills.
Showcase Your Projects:If you've worked on any data-related projects, whether in school or as a hobby, make sure to include them in your application. We love seeing practical applications of your skills, so don’t hold back on sharing your achievements!
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s straightforward and ensures your application goes straight to the right people. Plus, we’re excited to see what you bring to the table!
How to prepare for a job interview at QINETIQ LIMITED
✨Know Your Data Science Basics
Brush up on your statistics, machine learning techniques, and Python skills. Be ready to discuss how you've applied these in your projects or studies. This shows you’re not just familiar with the concepts but can also implement them effectively.
✨Showcase Your Projects
Prepare to talk about any relevant projects you've worked on, whether academic or personal. Highlight your role, the challenges you faced, and how you overcame them. This gives the interviewers insight into your problem-solving abilities and practical experience.
✨Understand QinetiQ's Work
Familiarise yourself with QinetiQ’s focus areas, especially in data analysis and sensor design. Being able to relate your skills to their projects will demonstrate your genuine interest in the company and the role.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, ongoing projects, or the technologies they use. This not only shows your enthusiasm but also helps you gauge if the company culture aligns with your values.