British Antarctic Survey
CambridgeDescription Skills specification How to apply Description
The British Antarctic Survey (BAS) is looking for a Data Scientist to join the Atmosphere, Ice and Climate team.
The successful candidate will have experience with data processing and analysis and writing efficient code. You will need strong skills in mathematics, statistics and computer programming, with experience using Python, Git and Machine Learning packages.
To work with environmental scientists and engineers to apply machine learning algorithms on pre-existing datasets.
A Master’s degree in a quantitative subject (or equivalent).
* Pre-processing data, including satellite imagery and large N-dimensional gridded products
* Applying and optimising machine learning algorithms
* Liaising with BAS environmental scientists and machine learning engineers at The Alan Turing Institute (ATI)
* Develop proof-of-concept studies to help support large grant proposals
* Manage code on GitHub (or equivalent)
* Any other duties as required by the Director
On-line application forms and further information are available on our website at
These are also available from the Human Resources Section, British Antarctic Survey, High Cross, Madingley Road, Cambridge, CB3 0ET. Tel: 221508.
Please quote reference: BAS 49/19
Closing date for receipt of application forms is: 28th April 2019
Interview date: 10th May 2019
Proposed start date: As soon as possible
BAS is an Equal Opportunity employer. As part of our commitment to equality, diversity and inclusion and promoting equality in careers in science, we hold an Athena SWAN Bronze Award and have an active Equality, Diversity and Inclusion programme of activity. We welcome applications from all sections of the community. People from ethnic minorities and disabled people are currently under-represented and their applications are particularly welcome. We operate a guaranteed interview scheme for disabled candidates who meet the minimum criteria for the job. We are open to a range of flexible working options including part-time or full-time employment as well as flexible hours due to caring or other commitments.