At a Glance
- Tasks: Join a dynamic team to analyse data and apply machine learning techniques.
- Company: QinetiQ, an inclusive tech company focused on data science and engineering.
- Benefits: Competitive salary, flexible working, coaching, and 25 days holiday.
- Other info: Great career growth opportunities and a chance to work on innovative projects.
- Why this job: Make a real impact with cutting-edge technology in a supportive environment.
- Qualifications: Studying Computing, Data Science, or related fields; Python and machine learning experience preferred.
The predicted salary is between 26400 - 26400 € 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
How to apply: Please fill in the application and include both a CV and a covering letter.
Our Benefits:
- 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
- Flexible Benefits package
- 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.
Recruitment Process: We want to make sure that our recruitment process is as inclusive as possible and we aspire to bring out the best in our candidates by creating an environment where everyone feels valued, heard and supported. If you have a disability or health condition that may affect your performance in certain assessment types, please speak to your recruiter about potential reasonable adjustments. QinetiQ is a place where you’ll be able to make a real difference. You’ll be part of an inclusive culture that values diversity, rewards integrity and merit, and where you’ll be empowered to fulfil your potential. We welcome candidates from all backgrounds, come and be part of our team!
Closing date for new applicants: 22nd May 2026
Data Scientist Year in Industry Placement- Farnborough or Malvern employer: QinetiQ
At QinetiQ, we pride ourselves on fostering an inclusive and dynamic work environment where diverse perspectives are not only welcomed but celebrated. As a Data Scientist in our Malvern or Farnborough locations, you'll benefit from extensive learning opportunities, a supportive culture that encourages collaboration, and the chance to work on cutting-edge projects that make a real impact. With a strong focus on employee growth, flexible working arrangements, and a comprehensive benefits package, QinetiQ is an excellent employer for those seeking meaningful and rewarding careers in data science.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist Year in Industry Placement- Farnborough or Malvern
✨Tip Number 1
Network like a pro! Reach out to current or former employees at QinetiQ on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by brushing up on your technical skills. Make sure you can talk confidently about Python, machine learning, and any relevant projects you've worked on. We want to see your passion and expertise shine through!
✨Tip Number 3
Show off your problem-solving skills! During interviews, be ready to tackle hypothetical scenarios or case studies. Think out loud so we can see your thought process and how you approach challenges.
✨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 our team at QinetiQ.
We think you need these skills to ace Data Scientist Year in Industry Placement- Farnborough or Malvern
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Scientist role. Highlight relevant skills like Python, machine learning, and any projects you've worked on that relate to data analysis. We want to see how your experience aligns with what we're looking for!
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 you can contribute to our team. Be sure to mention any specific experiences that demonstrate your skills and enthusiasm.
Showcase Your Projects:If you've worked on any cool projects, whether in school or as a hobby, make sure to mention them! We love seeing practical applications of your skills, especially if they involve data analysis or machine learning techniques.
Apply Through Our Website:Don't forget to apply through our website! It’s the best way to ensure your application gets to us directly. Plus, you'll find all the details you need about the role and our company culture there.
How to prepare for a job interview at QinetiQ
✨Know Your Data Science Basics
Make sure you brush up on your data science fundamentals, especially statistics and machine learning techniques. Be ready to discuss how you've applied these concepts in your academic projects or hobbies.
✨Show Off Your Coding Skills
Since coding is a big part of the role, practice writing Python code before the interview. You might be asked to solve a problem on the spot, so being comfortable with coding challenges will give you an edge.
✨Prepare for Team Dynamics
Understand the importance of teamwork in data science. Be prepared to share examples of how you've collaborated with others on projects, and think about how you can contribute to a diverse team environment.
✨Engage with Real-World Applications
Familiarise yourself with real-world applications of data science, especially in areas like sensor design and data analysis. Being able to discuss how data can drive decisions in various industries will impress your interviewers.