Data Scientists & Data Engineers

  • Civil Service
  • Part Time
  • Porton Down
Civil Service

Job Description

We are the AI Research and Applied Data Science teams in Dstl; teams of multi-disciplinary scientists, analysts, engineers and consultants. As part of the Intelligence Systems and Analytics Group in Dstl, we research novel AI and Data Science applications and help deploy them directly with Defence and Security partners (e.g. Defence Intelligence, UK Special Forces, F-35 project teams), partners across UK Government, and internationally (especially in the 5-Eyes community).

We implement a variety of traditional engineering, numerical and statistical approaches together with state-of-the-art machine learning and deep neural networks to a huge variety of applications, including:

Image and video analytics

Text analytics and natural language processing

Radar, radio frequency and acoustics analysis

Computer network and host log analysis

Data collection, processing, fusion and visualisation

Big data engineering and data flow orchestration

Not everything we do is highly classified. We love to publish academic papers and file patents. We've used open competitions (e.g. Kaggle) to access the very best worldwide expertise in machine vision. And we've sought to harness the power of the open source software community through the release of various tools on Github, for example Baleen and Stone Soup (https://github.com/dstl).

We give our people the freedom to think and innovate; working with like-minded scientists passionate about delivering quality technical solutions in a friendly and encouraging environment. And we offer loads of opportunities to keep up-to-date with the latest developments, through training and scholarships, attending and presenting at conferences, and working closely with industry and academic colleagues.ResponsibilitiesWe need great people! We're looking for those with: The ability to apply statistical rigour, critical thinking and creative problem solving to a variety of data sets (e.g. text, imagery, geospatial, time-series), seeking out new, high-risk, high payoff technologies.

A passion for programming in modern languages, and a solid understanding of relevant architectures (see more below)

A natural curiosity and independent drive to research, experiment and understand

Enthusiasm and experience in applying AI, ML and Data Science techniques to complex problems.

For senior roles, leadership and collaboration experience

For deployed roles, a willingness and ability to work domestically and overseas, sometimes in operational environments

Important Information Our work in defence, security and intelligence requires our employees to be British Citizens who are able to gain a high level of security clearance to understand the work you will undertake to protect us from any security threats. For this reason, we regret that only UK Nationals will be able to apply for this role. If you are an international or dual-national candidate, and you think you have the skills we need, please consider applying to any of our government, security or defence partners.

This role will require full UK security clearance and you should have resided in the UK for the past 5 years. For some roles Developed Vetting will also be required, in this case you should have resided in the UK for the past 10 years.

If you are a current Dstl employee, you are encouraged to inform your line manager of your application as they can support you through the process and should you be successful it will help in negotiating a release date.

Work location Dstl is strongly encouraging blended and flexible working either at one of our sites or from home or both. We want to empower you to undertake your duties at the most appropriate location for the task, however you will be allocated a Dstl site as a base. You may be required to travel to other Dstl and MoD sites as required.

We particularly welcome female and ethnic minority applicants and those from the LGBTQI community, as they are under-represented within Dstl at these levels.

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