Liz is a Data Scientist with experience in natural language processing, machine learning, data analytics, agent-based modelling and evolutionary game theory. She applies these skills to areas such as the labour market, research funding, searching for policy impact, and modelling human behaviour. She currently works at Nesta, where she works on several projects involved extracting information from job advert text to understand the labour market.
There is no publicly available data on the skills that are commonly required in UK online job adverts, despite this information being useful for a range of use cases. To address this, we have built an open source skills extraction python library using spaCy and huggingface. Our approach is twofold: we train a named entity recognition model to extract skill entities from job adverts then map them onto any standardised skills taxonomy. By applying this algorithm to a dataset of scraped online job adverts, we are then able to find skill similarities amongst occupations, and regional differences in skill requirements.