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.
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.
The Data Analytics teams within AMS 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/Nebula) 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.
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:
As a global company of over 6,000 dedicated people providing technological and scientific expertise, we are excited to recruit the most talented and enthusiastic people to become key parts of our business. Our Early Careers programmes give you the opportunity to be at the heart of impactful projects.
In our unique working environment, teams from different backgrounds collaborate widely on some of the world’s most complex defence and security challenges. Whatever part you play, you’ll get to experience what happens when we all share different perspectives, blend disciplines, and link technologies. It’s a diverse and inclusive environment where you can be authentic, feel valued and realise your full potential. Together, we’ll explore new ways of protecting the world around us.
Looking after the health and wellbeing of our employees are our top priority. We offer a host of services designed to support your wellbeing. They range from our Thrive app and Employee Assistance Programme to Mental Health First Aiders. The wellbeing of our employees is critical to our collective and individual success.
We offer global career progression and the opportunity to work on a broad range of interesting projects along with a wide range of rewards and recognition. Our highly competitive salaries come with a raft of benefits, from a performance-based Employee Incentive Scheme to Thank Q, our global recognition scheme. There’s also a Share Incentive Plan, Life Assurance and Benefits+, our flexible benefits package. It’s all designed to make life easier for you.
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