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It’s an exciting time to join one of our Early Careers programmes at QinetiQ. We are always looking for great people to join our team, whether you are taking your first steps in starting a career or you are looking to make a career change, we have a wide range of exciting opportunities for you.
Data Analytics
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.
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 and take sound, evidence-based actions.
We have a strong pedigree in data science, data analysis 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.
What will I be doing?
The Data Analytics 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) and many roles in between. Our daily work involves applying both conventional and novel machine learning techniques to customer problems as appropriate and can cover 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. We frequently work with colleagues from Human Behaviour, Autonomy and Applied Science and other areas to provide cross-domain insight and we are increasingly using deep neural net-based AI and cloud technologies (AWS, Azure etc.) to build solutions.
In this role you will gain practical experience in the data analytics process from data collection and data wrangling through to generating conclusions and results. This includes the exploration and visualisation of data to answer real-life questions. 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 experience in the soft skills of planning, technical report writing, and presentation.
Academic requirements
You will need to have obtained or be studying towards at least a 2:2 in a degree with a key focus on any of the disciplines listed below:
- 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
Mandatory
In accordance with our National Security Vetting requirements, all applicants must also be eligible for SC clearance as a minimum.
Please note that under immigrations rules, our Early Careers roles do not meet the legal threshold for candidates who are residents of the UK on student visas.
