Matt Hodgskiss
About Matt Hodgskiss
Matt Hodgskiss is an Associate Director of Scientific Data Engineering at Exscientia, with a background in data science and software development. He has previously held leadership roles at Medicines Discovery Catapult and Health and Safety Laboratory, and he holds advanced degrees from the University of Manchester and Durham University.
Current Role at Exscientia
Matt Hodgskiss serves as the Associate Director of Scientific Data Engineering at Exscientia. He has held this position since 2022, contributing to the company's focus on integrating data science with drug discovery. His role involves overseeing data engineering initiatives that support scientific research and development within the organization. Exscientia is known for its innovative approach to artificial intelligence in drug design, and Hodgskiss plays a key role in advancing these efforts.
Previous Experience at Medicines Discovery Catapult
Prior to his current role, Hodgskiss worked at Medicines Discovery Catapult as the Head of Data Science from 2018 to 2022. In this position, he led data science initiatives aimed at enhancing drug discovery processes. His tenure at the Catapult allowed him to develop and implement data-driven strategies that supported various research projects in the pharmaceutical sector.
Background in Data Science and Software Development
Before his role at Medicines Discovery Catapult, Hodgskiss was the Technical Team Lead for Data Science and Software at the Health and Safety Laboratory from 2013 to 2018. His responsibilities included managing data science projects and software development efforts. Additionally, he worked as a GIS Software Developer at Stockport Council from 2008 to 2013, where he focused on geographic information systems and software solutions.
Education and Academic Qualifications
Hodgskiss holds an MSc in Science and Engineering in Medicine and Biology from the University of Manchester, which he completed in 2005. He also earned a BSc in Natural Science from Durham University, where he studied Mathematics, Physics, and Chemistry from 2000 to 2003. His educational background provides a strong foundation for his work in scientific data engineering and data science.