Job Title:
Data Scientist Apprentice
Location:
Farnborough, England, United Kingdom
Role Type:
Early Careers – Apprenticeship
Job Title: Data Scientist Apprenticeship
Job Location: Farnborough
Job Type: Permanent, Fulltime
Salary: £27,150
Job ID: 19996
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.
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 of planning, technical report writing, and presenting.
Apprenticeship details:
Title: Level 6 Data Scientist Apprenticeship
Qualification: BSc (Hons) Data Science
Course provider: Cranfield
Provider Link: https://www.cranfield.ac.uk/mku/mku-data-scientist
Academic requirements:
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)
How to apply:
Please fill in the application and include both a CV and a covering letter.
Our Benefits (the list is 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
Flexible Benefits package
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.
QinetiQ is a place where you’ll be able to make a real difference. You’ll be part of an inclusive culture that values diversity, rewards integrity and merit, and where you’ll be empowered to fulfil your potential. We welcome candidates from all background, come and be part of our team!
To find out more about Life at QinetiQ, please see the link: Life at QinetiQ
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