Cambridge, GB

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At Featurespace, we invest heavily in R&D to ensure our models remain the best in the industry. We’re proud to have been recognised not only with several awards but also to have been met with an enthusiastic reception in the market place.

Featurespace are looking for a Research Scientist – Deep Learning to join our Deep Learning team based in our Cambridge office. You will join a diverse team of researchers, with a variety of backgrounds, that enjoy sharing new ideas in a supportive and collaborative environment.

In your role as Research Scientist – Deep Learning,  you will be responsible for researching and prototyping advanced statistical models, algorithms and data workflows that improve Featurespace analytical products, and designing and supporting our deep learning technology.

We offer the chance to deliver real impact and see your work protect tens of millions of people across the world from fraud in real time.


Day to Day

  • Interface with stakeholders within the business to understand analytical requirements and opportunities
  • Research new machine learning algorithms and statistical techniques to solve problems in the detection and prevention of financial crime, with a special focus on deep learning
  • Contribute to the productionisation of new analytical features through prototyping, requirements setting and implementation
  • Provide research input into future analytical strategies and product development
  • Participate in the planning and review processes for work in the Deep Learning team
  • Share knowledge of analytical techniques and tooling across delivery and engineering teams
  • Create and deliver patents, publications and external talks as appropriate

About you

Must haves:

  • Academic background at postgraduate level in a relevant discipline, e.g. Mathematics, Statistics, Computer Science, Physics, or Engineering
  • Familiarity with neural networks at a mathematical level
  • Experience in using Python, Java, C++ or another high-level programming language
  • Ability to write clean code
  • Experience using a deep learning framework such as TensorFlow or PyTorch
  • Ability to manage and prioritise personal workload


Great to haves:

  • PhD or post-doctoral research experience in a relevant discipline
  • Publications advancing theoretical knowledge in a relevant discipline
  • Familiarity with modern software engineering practices (including Git, IDEs, testing and code review)
  • Familiarity with statistical reasoning
  • Experience in working with large datasets

Personal Qualities

The work is often challenging and fast paced. We are looking for someone who has the following qualities:

  • Enjoys working in a team of like-minded and intelligent people to solve complex problems
  • A focus on personal achievement and responsibilities
  • A passion to learn new skills and technologies
  • Attention to detail
  • A passion to work for one of the fastest growing fraud prevention technologies in the world
  • Enthusiasm


And most importantly, a small-company attitude: willingness to adapt to a variable role and a great can-do attitude.

Apply now