At a Glance
- Tasks: Join a dynamic team to analyse data and apply machine learning techniques.
- Company: Innovative tech company focused on data-driven solutions.
- Benefits: Access to on-demand learning, coaching, and 25 days holiday.
- Other info: Flexible working environment with opportunities for growth and collaboration.
- Why this job: Gain hands-on experience in data science and make a real impact.
- Qualifications: GCSE Maths and English, A-Level Maths, and programming experience.
The predicted salary is between 18000 - 25000 £ per year.
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.
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 our apprentice working as part of small project teams. You will attend project meetings, be involved in data preparation, and applying the relevant Machine Learning or Artificial Intelligence techniques. You will over time, 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. In this role you will gain practical experience in the full end to end data pipeline from data collection, data wrangling and modelling through to generating conclusions and results. You will gain knowledge of statistical techniques such as supervised and unsupervised machine learning algorithms, develop programming skills in Python and for the Cloud, as well as general data analysis techniques. You will also gain soft skills such as planning, technical report writing, and presenting.
Grade 5 in GCSE Mathematics or equivalent, Grade 4 in GCSE English Language or equivalent (prior to admission) with BBC at A-Level to include Maths. We will not accept A-Levels Citizenship Skills, General Studies, and Critical Thinking. or Level 4 Data Analyst apprenticeship at Merit or Distinction.
Additional requirements
- You must be able to travel to the training provider for the academic elements of the Level 6 Apprenticeship. Expenses for travel will be reimbursed in line with our expenses policy;
- Some understanding of statistics (statistical analysis) and/or mathematical modelling;
- Some experience of programming in at least one coding language e.g. Python, R, C++;
- Some familiarity or experience with basic coding best practices e.g. version control and code quality.
Beneficial
- Experience with any cloud computing platform
- Machine learning or data analysis project experience (through academia or personal projects)
- Evidence of soft skills, including; Examples of working in a team, technical communication (written or oral)
Our Benefits (not exhaustive)
- On demand learning, access to courses, modules, and lectures via multiple digital learning platforms
- Coaching and Mentoring
- 25 days annual holiday excluding
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 data scientists or apprentices on LinkedIn. Ask them about their experiences and any tips they might have. This can give you insider knowledge and potentially lead to referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, whether they're from school or personal endeavours. Make sure to include any machine learning techniques you've used. This will help us see your practical experience in action.
✨Tip Number 3
Prepare for interviews by brushing up on common data science questions and coding challenges. Practice explaining your thought process clearly, as communication is key in our team. We want to see how you approach problems!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Data Scientist Apprentice
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Data Scientist Apprentice role. Highlight any relevant projects or coursework, especially those involving data analysis or programming in Python.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data science and how your background makes you a great fit for our team. Be specific about your experiences and how they relate to the job description.
Showcase Your Projects: If you've worked on any data-related projects, whether in school or on your own, make sure to mention them! We love seeing practical applications of your skills, so include links or descriptions of your work.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at QINETIQ LIMITED
✨Know Your Data
Make sure you brush up on your understanding of data types and the data lifecycle. Be ready to discuss how you've worked with numerical data, natural language processing, or any other relevant data types. Showing that you can connect your experience to the role will impress the interviewers.
✨Showcase Your Coding Skills
Since programming is a key part of this role, be prepared to talk about your experience with coding languages like Python or R. Bring examples of projects where you've applied coding best practices, such as version control. If you can, demonstrate your problem-solving approach through a coding challenge or example.
✨Understand Machine Learning Basics
Familiarise yourself with both supervised and unsupervised machine learning algorithms. Be ready to explain these concepts in simple terms and discuss any projects where you've applied them. This shows that you not only understand the theory but can also apply it practically.
✨Communicate Effectively
Soft skills are just as important as technical skills. Prepare to share examples of how you've worked in teams, communicated technical information, or presented findings. Practising your responses will help you convey your thoughts clearly and confidently during the interview.