Open to graduate data roles — London or remote

Roland
Oteniya

Data scientist in London. MSc Data Science & AI, distinction, University of Liverpool — mechanical engineer before that. I work on time-series forecasting and the unglamorous data plumbing that has to exist before any model is worth running.


Selected work

  1. Forecasting S&P 500 volatility with deep learning MSc dissertation. Benchmarked LSTM variants against ARIMA and GARCH, then built a hybrid of the two. The hybrid lost — and why it lost is the interesting part. Python · PyTorch · Time series · 2025–26
  2. Wildfire detection with CNNs — literature review Compared conventional convolutional networks against CNNs using Learning without Forgetting, for more efficient continual wildfire detection. Deep learning · Computer vision · Review

Writing

All essays →


Looking for a graduate data scientist or analyst

London-based, open to remote. If you're hiring, or you just want to argue about whether hybrid models are ever worth it, get in touch.