Data scientist with experience providing actionable insights through using computational models and machine learning methodology in multiple sectors. Key elements of my work involve providing remaining useful life statistics, event based maintenance alerts & running cost/emission reduction in the rail and energy industry. Proficient use of Python & R for data manipulation and machine learning engineering, often in the realm of time-series data where forecasting and abnormality detection requires added contemplation.Previously worked as a research intern with UCL on the VPHAS+ astronomical survey. My role was to process and clean the compiled image fields and retrieve the relevant photometric data for further identification of certain stellar objects using Python. Specifically, identifying emission-line stars in the Milky Way, introducing unsupervised machine learning to improve the established methods allowing for hidden emission-line stars to also be found. The result will be the most comprehensive catalogue of emission-line stars in the southern Galactic plane to date.Prior to this I attended UCL where I graduated with a MSc in Astrophysics.