Nathan Steer begins his career with DataDiligence!
He joins us as a Data Associate having recently graduated from the University of Manchester with a Masters in Astronomy & Astrophysics – where his thesis drew on advanced machine learning techniques to find the ideal model to classify SDSS (Sloan Digital Sky Survey) data. The resultant models found that the data was able to be identified with an accuracy of 98.24% using only ~25,000 datapoints, compared to the original ~300,000 datapoints needed*.
Commenting on why he decided to join DataDiligence, Nathan said:
“The diverse set of tasks and solutions that DataDiligence performs will help grow my skills in a wide variety of ways, some of which I haven't imagined yet!”
Nathan holds an MSc by Research, Astronomy & Astrophysics from the University of Manchester, and a BSc Astrophysics (first class) from the University of Hull.
He is a keen squash player and can’t wait to get back to regular matches. He also enjoys a variety of athletics, though is mostly focused on sprints, and watching Liverpool FC. Sports are not his only interest, as he enjoys science fiction classics such as I, robot and the Lensman series, the latter helping him identify physics as the area to study.
*The data in question involved using multiple spectroscopic redshift measurements rather than imaged photos of galaxies, quasars, and stars.