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- Tasks: Dive into data science, analysis, and engineering while working on real-world projects.
- Company: Join QinetiQ, a forward-thinking company that values diversity and collaboration.
- Benefits: Gain hands-on experience, mentorship, and opportunities for career advancement.
- Other info: Exciting apprenticeship with travel opportunities and a focus on AI and Machine Learning.
- Why this job: Make a difference in the UK Ministry of Defence with cutting-edge technology and data insights.
- Qualifications: Strong maths and physics skills; coding experience in Matlab, Python, or C++ is a plus.
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.
In Mission Systems our role is to ensure our customers get the most out of their data. Our aims are to ensure: that starting data is of the highest quality; that it is quickly and efficiently processed into clear, meaningful information; that we extract deeper insight from it; and that we provide robust, data-led advice to our customers, and take sound, evidence-based actions. Our work is an exciting blend of maths, physics, engineering, computer science and IT. We are at the cutting edge for designing and applying tools, software and automation techniques that enable the rapid and timely transfer of relevant data and information. We have established teams working in Lincoln with direct connections to other experts in places like Malvern, Farnborough and Portsmouth. Additionally, we have dedicated teams who are embedded with the customer at RAF Coningsby, RAF Marham and RAF Waddington. These teams support the UK Ministry of Defence, in particular the Royal Air Force, in the processing, assimilation, analysis and fusion of data.
Through your academic studies, you will be expected to gain an in-depth knowledge of data science, analysis, engineering, and manipulation. Your skills and knowledge will be augmented by working on research tasks and real-world projects that enhance the operational effectiveness of platforms and systems. You will be provided with opportunities to gain expertise in Digital Modelling, AI, and Machine Learning.
Key Capabilities
- Strong Maths and Physics
- Have an interest and/or experience within computer coding. Matlab, Python, C++ experience is beneficial but not essential.
- Leadership skills OR experience in leadership, this can be via hobbies or education.
- You must be able to travel to the training provider for the academic elements of the Level 6 Apprenticeship.
Data Scientist Apprentice employer: QINETIQ LIMITED
Contact Detail:
QINETIQ LIMITED Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist Apprentice
✨Tip Number 1
Network like a pro! Reach out to current employees at QinetiQ on LinkedIn or through mutual connections. Ask them about their experiences and any tips they might have for landing the Data Scientist Apprentice role.
✨Tip Number 2
Prepare for the interview by brushing up on your maths and physics knowledge. Be ready to discuss how you’ve applied these skills in real-world scenarios, as well as your coding experience with languages like Python or Matlab.
✨Tip Number 3
Showcase your leadership skills! Whether it’s through school projects, clubs, or even sports, be prepared to share examples of how you’ve led a team or taken initiative. This will highlight your potential to thrive in a collaborative environment.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining the QinetiQ team.
We think you need these skills to ace Data Scientist Apprentice
Some tips for your application 🫡
Show Your Passion for Data: When you're writing your application, let your enthusiasm for data science shine through! Share any relevant projects or experiences that highlight your interest in maths, physics, and coding. We want to see how you connect with the role!
Tailor Your Application: Make sure to customise your application to fit the job description. Highlight your skills in data analysis, engineering, and any coding experience you have. We love seeing how your unique background can contribute to our inclusive workplace!
Be Clear and Concise: Keep your writing straightforward and to the point. Use clear language to explain your experiences and skills. We appreciate applications that are easy to read and get straight to the good stuff!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at QINETIQ LIMITED
✨Know Your Data Science Basics
Make sure you brush up on your data science fundamentals. Be ready to discuss concepts like data manipulation, analysis, and the tools you’ve used, such as Python or Matlab. Even if you’re not an expert yet, showing enthusiasm and a willingness to learn can really impress.
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've tackled challenges in your studies or projects. Use specific examples that highlight your analytical thinking and how you approached data-related problems. This will demonstrate your ability to apply theoretical knowledge to real-world situations.
✨Emphasise Teamwork and Leadership
Since QinetiQ values collaboration, think of instances where you’ve worked in a team or taken on leadership roles, even in informal settings. Share how you contributed to group success and what you learned from those experiences. It’s all about showing you can work well with others!
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the projects you might work on or the technologies they use. This shows your genuine interest in the role and helps you understand if it’s the right fit for you.