At a Glance
- Tasks: Join a dynamic team to analyse data and apply machine learning techniques.
- Company: Innovative tech company focused on data science and engineering.
- 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 the full data pipeline and develop valuable programming skills.
- Qualifications: GCSE Maths and English, A-Level Maths, and some programming experience required.
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 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.
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.
Data Scientist Apprentice in Malvern employer: QINETIQ LIMITED
Contact Detail:
QINETIQ LIMITED Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist Apprentice in Malvern
✨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 maybe even a referral!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning or data analysis. This is your chance to demonstrate what you can do beyond just a CV.
✨Tip Number 3
Prepare for interviews by practising common data science questions. Brush up on your coding skills in Python and be ready to discuss your thought process when solving problems. We want to see how you think!
✨Tip Number 4
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 StudySmarter. Don’t miss out!
We think you need these skills to ace Data Scientist Apprentice in Malvern
Some tips for your application 🫡
Show Your Passion for Data: When writing your application, let us see your enthusiasm for data science! Share any personal projects or experiences that highlight your interest in data analysis and machine learning. This will help us understand why you're excited about joining our team.
Tailor Your Application: Make sure to customise your application to fit the role of Data Scientist Apprentice. Highlight relevant skills like programming in Python or any experience with statistical techniques. We want to see how your background aligns with what we do at StudySmarter!
Be Clear and Concise: Keep your writing clear and to the point. Use straightforward language and avoid jargon unless it's necessary. We appreciate a well-structured application that makes it easy for us to see your qualifications and potential.
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 helps us keep everything organised on our end.
How to prepare for a job interview at QINETIQ LIMITED
✨Know Your Data
Familiarise yourself with different types of data and their applications. Brush up on your understanding of numerical data, natural language processing, and signals analysis. Being able to discuss these topics confidently will show that you're ready to dive into the role.
✨Showcase Your Coding Skills
Make sure you can talk about your programming experience, especially in Python or any other relevant languages. Bring examples of projects you've worked on, whether academic or personal, to demonstrate your coding abilities and understanding of best practices.
✨Prepare for Team Dynamics
Since you'll be working in small project teams, think of examples where you've successfully collaborated with others. Be ready to discuss how you communicate technical information clearly, both in writing and verbally, as this is crucial for stakeholder engagements.
✨Understand Machine Learning Basics
Brush up on your knowledge of supervised and unsupervised machine learning algorithms. Be prepared to discuss how you would apply these techniques to real-world problems, as this will highlight your analytical thinking and problem-solving skills.