The Opportunity
As a Research Scientist, you will help us to achieve our goals and deliver success on behalf of our customers by researching and prototyping advanced statistical models, algorithms, and data workflows that improve Featurespace analytical products. You will be responsible for designing and supporting our machine learning and AI technology alongside a diverse team of research scientists and engineers.
This is a hybrid role based in our Cambridge office, so you will ideally be comfortable coming into the office once or twice a week. If you’re interested in the role but require more flexibility, please speak to us!
Day to Day
1. Interface with stakeholders within the business to understand analytical requirements and opportunities
2. Research new machine learning algorithms and statistical techniques to solve problems in the detection and prevention of financial crime
3. Create and deliver patents, publications and external talks as appropriate
4. Contribute to the productionisation of new analytical features through prototyping, requirements setting, and implementation
5. Provide research input into future analytical strategies and product development
6. Participate in the planning and review processes for work in the Innovation Lab
7. Share knowledge of analytical techniques and tooling across delivery and engineering teams
About you
Must haves:
8. Academic background at postgraduate level in a relevant discipline, e.g. Mathematics, Statistics, Computer Science, Physics, or Engineering
9. Familiarity with neural networks at a mathematical level
10. Experience in using Python, Java, C++ or another high-level programming language
11. Ability to write clean code
12. Experience using a deep learning framework such as TensorFlow or PyTorch
13. Ability to manage and prioritise personal workload
Great to haves:
14. PhD or post-doctoral research experience in a relevant discipline
15. Publications advancing theoretical knowledge in a relevant discipline
16. Familiarity with modern software engineering practices (including Git, IDEs, testing and code review)
17. Familiarity with statistical reasoning
18. Experience in working with large datasets
Equal Opportunities
Here at Featurespace we are committed to being a place of equality, inclusion and respect to provide a safe environment for you to bring your authentic self to work. We know that we gain as much strength from our differences as we do our similarities. We value diversity and are dedicated to listening and learning from each other to build and maintain a positive and productive culture. We appreciate this will be an ever-evolving focus for the business to ensure everyone feels supported and has a sense of belonging.