Dataffirm
A complex, real‑time Angular‑based web application leveraging machine learning on 'big data' and live market analytics to identify investment opportunities
In Detail
I joined this fintech startup during the very early development stages post‑funding. With a dispersed team of back‑end developers and data scientists based in London, Cyprus and South Africa, I was one of two front‑end developers working directly alongside their designer, analyst, and wider marketing teams.
Starting from scratch, the product was an evolving MVP: a responsive, Angular 2‑based platform using Sass. This was a near real‑time lightweight modern business intelligence tool that deploys machine learning against enormous sets of complex 'big data', live markets and a Java‑based marketing engine. The results allowed users to make informed quantitative investments and track their results.
Being in such an early stage when I joined, one of my responsibilities was to oversee the application through various different iterations and states, ensuring that, technically, the platform remained viable for any future expansion. Directed by investors, stakeholders, and user feedback, it is fair to say that there were a lot of evolutions.
The application itself featured a complex array of interactive data visualisation tools and tables. Whilst this was very much intended as a product to be used on a desktop machine, where more data could be consumed in one go, we also focused heavily on making sure that mobile and tablet users could still access the platform, albeit in a cut‑down form.