Data Analyst

Job reference:
BAS 21/136
Contract type:
Full Time
Duration:
Until March 2023
Salary:
£39,748 - £50,790 per annum
Benefits:
We offer generous benefits
Team:
British Antarctic Survey
Location:
Cambridge
Closing date:
24 October, 2021 11:59 pm

Description

The British Antarctic Survey’s Artificial Intelligence Lab is looking for a Machine Learning Engineer to join a team working on the initial stages of a Digital Twin of the Royal Research Ship Sir David Attenborough.

Who we are

British Antarctic Survey (BAS) delivers and enables world-leading interdisciplinary research in the Polar Regions. Its skilled science and support staff based in Cambridge, Antarctica and the Arctic, work together to deliver research that uses the Polar Regions to advance our understanding of Earth as a sustainable planet. Through its extensive logistic capability and know how BAS facilitates access for the British and international science community to the UK polar research operation. Numerous national and international collaborations, combined with an excellent infrastructure help sustain a world leading position for the UK in Antarctic affairs.

British Antarctic Survey is a component of the Natural Environment Research Council (NERC). NERC is part of UK Research and Innovation www.ukri.org We employ experts from many different professions to carry out our Science as well as to keep the lights on, feed the research and support teams and keep everyone safe! If you are looking for an opportunity to work with amazing people in amazing places, then British Antarctic Survey could be for you. We aim to attract the best people for those jobs.

Purpose

The initial focus will be to identify how Machine Learning can be applied to the data collected on-board the ship, and to develop and deploy suitable models and methods. The successful candidate will join the BAS AI Lab, contributing to its ongoing activities and to the development of the AI Lab community. Candidates will have experience in managing, structuring and analysing data, working with large data sets and building ML systems in Python, Julia, or similar languages.

Qualification

A PhD or equivalent experience in a relevant field

Duties

  • To deploy Machine Learning in the context of the RRS Sir David Attenborough.
  • To work collaboratively with researchers and senior investigators from across BAS, and with external partners as required.
  • To undertake other duties as appropriate as requested by the BAS Director.

Please quote reference for any queries: BAS 21/136
Publication date: 8 October 2021
Closing date for receipt of application forms is: 24 October 2021
Interviews are scheduled to be held on: 11 November 2021

At BAS, our vision is to be a world-leading centre for polar science and operations. Making our vision a reality depends on the excellence and diversity of our staff. We are committed to creating a workplace where all our staff can flourish and succeed. BAS is a Disability Confident employer, we are proud to hold a bronze Athena Swan award and we are a member of enei, the Employers Network for Equality & Inclusion.

We appreciate the importance of achieving work-life balance and support this with a number of family and carer-friendly policies. Plus a flexible working policy for those who may wish to amend their working pattern or arrangement.

Skills are listed as either Essential or Desirable. Desirable skills importance rating in parenthesis (1 is high, 5 is low)

Communication skills

  • Excellent written and verbal communication skills - Essential
  • Ability to communicate more complex, specialist, or conceptual information clearly and persuasively - Essential
  • Experience in the visual representation of quantitative data - Desirable [2]

Computer / IT skills

  • Excellent computer skills - Essential
  • Proficiency in one or more modern statistical programming languages used in research in data science and machine learning, such as Python or Julia - Essential
  • Experience of working with large datasets and writing scalable code - Essential
  • Experience in computational statistics, particularly Bayesian modelling and Bayesian statistics - Desirable [2]
  • Contribution and engagement with open-source software communities - Desirable [2]

Decision Making

  • Able to make decisions independently and as part of a team - Essential

Interpersonal skills

  • Ability to interpret and share knowledge - Essential
  • Ability to foster an innovative and creative environment for research - Desirable [2]

Numerical ability

  • Significant experience in developing and applying predictive models - Essential

Other Factors

  • Willingness to be flexible and responsive to changing requirements - Essential
  • Record of ongoing development of technical skills and knowledge - Desirable [2]

Qualifications

  • A PhD or equivalent experience in a relevant field - Essential

Resource Management ability

  • Experience in managing, structuring, and analysing research data - Essential
  • Ability to work independently, and collaborate productively as part of a team - Essential

Skills / Experience

  • Expertise in state-of-the-art methods in data science and computational intelligence - Essential

In order to apply, please complete and upload all the application forms listed below. If you experience any issues in uploading your Application Form, please email us your complete application, making reference to the job reference and title.

If you are an EU, EEA or Swiss citizen, please visit this website before applying.

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Due to the COVID-19 outbreak, the Recruitment team is working remotely and cannot access the building. If you would like to apply for this job but cannot apply online, please contact us: [email protected]

If you need more information

Email
[email protected]
Telephone:
+44 (0)1223 221400
Facsimile:
+44 (0)1223 362616

The information you provide during the application process will only be used for the purpose of progressing your application, to fulfil legal or regulatory requirements where necessary or, in the case of the Equal Opportunities Monitoring Questionnaire, to help BAS meet its equal opportunities policy.

The British Antarctic Survey will not share the information you provide with any third parties, and the information will be held securely by the British Antarctic Survey whether the information is in electronic or physical format. Please note that the Equal Opportunities Monitoring Questionnaire will be detached from your application prior to the short-listing of candidates for interview.

Unsuccessful applications will be securely destroyed 6 months after the end of the recruitment process (or 1 year after the end of the recruitment process in the case of Marine Staff and AEP. The applications of successful applicants will be retained as part of their personnel file.

Further information can be found in the information notice of NERC, our parent body.