Data Scientist

London, England, United Kingdom · Research


Signal is a revolutionary new technology platform built for analysing text and discovering market intelligence, developed in partnership with the world's leading academics. Our large-scale text analytics system unlocks knowledge and insight from unstructured textual data, enabling organisations to solve complex information challenges and providing a competitive advantage for our clients. Our media monitoring product, built on top of our technology, is enabling organisations to solve real-time complex information challenges (e.g. “All the news related to IPOs of European technology companies”).

We are looking for talented data scientists passionate about quick iteration cycles in multi-disciplinary teams and the creation of prototypes in order to explore several ways of solving client problems using data science principles. The selected candidate will work in one of our Agile Product teams, alongside developers and UX / UI Designers, data scientists, and data engineers. The main goal of the role will be to help discover clients problems, and explore the feasibility and value of early iterations of solutions to these problems. The candidate will also work closely with our Research team, which focuses on the long-term improvement of different components and solutions.

Main Responsibilities

The ideal candidate will have a strong development background with experience on product development using Machine Learning principles, libraries and frameworks. We are looking for someone who can understand our clients challenges, propose methods to solve problems, experiment with different alternatives to address it, build them as prototypes and finally deployed the most successful ones in production. Team work and learning are two of the pillars at Signal and for this reason, we are looking for individuals who are open-minded, inquisitive and have the desire to learn new skills from everyone in the company.

Our current stack:


Desirable skills and qualifications:

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