Date Posted:
2026-05-08
Country:
United Kingdom
Location:
Gloucester, South Gloucestershire
Position Role Type:
Onsite
Data Scientist & Machine Learning Researcher
Gloucester, Manchester
Benefits:
1. £:Competitive salary
2. Contributory Pension Scheme (up to 10.5% company contribution)
3. 6 times salary ‘Life Assurance’ with pension
4. 25 days holiday (increasing with service) + statutory public holidays, plus opportunity to buy and sell up to 5 days (37hr)
5. Company bonus scheme (discretionary)
6. Flexible Benefits scheme with extensive salary sacrifice schemes, including HealthCashplan, Dental, and Cycle to Work amongst others
7. Enhanced sick pay
8. Enhanced family friendly policies including enhanced maternity, paternity & shared parental leave
Work Culture
9. 37hr working week, although hours may vary depending on role, jobrequirementor site-specific arrangements.
10. Early 1.30pm finish Friday, start your weekend early!
11. Remote,hybridand site based working opportunities, dependant on your needs and the requirements of the role.
12. Up to 5 paid days volunteering each year.
13. Flexible working culture focused on output, with more formal flexible working arrangements on request (assessed subject to role) - please highlight any requests to the Talent Acquisition team.
About the role
This role is within the Strategic Research Group (SRG). The SRG are a team of Data Science, Machine Learning and AI specialists who develop novel AI solutions to mission focussed problems. In this role you will be responsible for the technical development of AI/ML projects, working alongside more senior members of the team, supporting projects from initial idea scoping right through to final project delivery both in customer and internal domains.
You will demonstrate novel thinking and propose new ideas for solving challenging problems. You will communicate these ideas effectively to senior technical leaders to feed into technical direction of your projects.
Responsibilities
14. Develop, novel data science solutions, contributing significantly to machine learning projects as part of a team, with some guidance and direction from seniors.
15. Bring experience in developing and delivering data-centric solutions.
16. Undertake research and applied AI/ML tasks on both customer and internal research projects.
17. Work with autonomy on assigned tasks within project groups.
18. Generate ideas for new research directions.
19. Deliver AI/ML/Data Science solutions to broad range of problems in defence.
20. Work with more senior group members, customers and internal stakeholders to determine appropriate technical approaches and do the technical development required for delivery.
21. Excellent communication skills, prepared to present and undertake practical demonstrations of work internally in the team and to senior stakeholders with adaptability to audiences of different levels of technical expertise.
Skills & Experience
Essential
22. BSc in Machine Learning, Data Science, Computer Science, Mathematics or related field.
23. Experience coding in Python and associated ML packages (HuggingFace, TensorFlow, PyTorch).
24. Have experience of delivering ML solutions to stakeholders.
25. Demonstrate good understanding of AI/ML algorithms for different data types and tasks including Generative AI, NLP and computer vision, sufficient to be able to undertake research and development beyond existing literature, with some support and technical direction set by seniors.
26. Experience of training and developing AI models including Large Language Models.
27. Ability to produce high-quality scientific (academic style) writing for internal & external publication.
28. Problem solve with high levels of autonomy, with some input from technical leaders.
29. Be a self-starter, being pro-active in finding solutions.
Desirable
30. PhD. or Masters degree highlighting experience of academic research.
31. Experience using robust ML pipelines, appropriate version control and environment management (such as venvs or Docker)
32. Working knowledge of Linux systems, using basic commandline functionality (e.g. AWS CLI, Docker CLI, Linux commands like ssh, ls, cd…)
33. Experience working in Cloud, especially AWS but also equivalents such as GCP or Azure.
34. Research publications in peer reviewed journals.
35. Comfortable following agile processes for project delivery.
36. Experience of delivering AI/ML projects in defence or government.
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