Work

NLP Research Scientist, Schonfeld, London

Oct 2021 - Now

Schonfeld is an industry leading hedgefund offering a systematic trading platform. I work part-time, 10 hours a week, in the Quantitative Information Sciences (QIS) team. My research at Schonfeld is concerned with building machine learning models that can identify signals in natural language data sources, e.g., broker research reports, that correlate with security price behaviour on the stock market.

Deep Learning Researcher, UROP, MIL Lab, University of Cambridge

Jun 2019 - Sep 2019

My research was focused on building a deep learning system for the automation of Spoken Language Assessment (SLA) of non-native speakers. The system I built gave state-of-the-art results on the ALTA datasets.

Software Developer, Emotech LTD, London

Aug 2018 - Sep 2018

Emotech (at the time of my internship) was a start-up building an emotional artificial intelligence virtual assistant as a physical robot. My role as a software intern was to develop algorithms (in Golang) to traverse the robot's state machine graph for automation of test writing. Further, I used React and TypeScript to develop an internal dashboard to monitor the usage of the deployed robots.

Technology Risk Consultant, PwC, Birmingham

Jul 2018 - Aug 2018

As a technology risk intern, my work catered to technology firms and institutions, ranging from the education sector with universities migrating to cloud based servers to more fundamental research in the area of quantum computing and artificial intelligence as forms of emerging technologies.

Data Analyst, British Telecom, London

Jun 2017 - Sep 2017

I Trained a machine learning model (in R) to predict the SLA (Service Level Agreement) status (pass/fail) of incoming fault tickets (reported by BT customers) based upon the natural language descriptions of the faults. My model was successfully deployed.