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Data Science Internship 2020

Salary notes: 
£23,875 starting salary in London and £18,194 starting salary in Newcastle
Job/scheme locations: 
London and Newcastle
Type of opportunity: 
Internship
Application deadline: 
01/12/2019

The National Audit Office (NAO) supports Parliament to hold the government to account for the way public services are delivered. Our primary role is to scrutinise public spending for Parliament. We do this by certifying over 350 government accounts and produce around 65 Value for Money (VFM) reports each year.

We are looking to recruit candidates to participate in our year long, data science internship scheme starting on 1st September 2020 for the London interns and 28th Aug 2020 for the Newcastle interns.

Towards the end of the internship the interns may have the opportunity to make a fast-track application for a permanent Analyst position at the NAO.

Responsibilities

We expect you will spend your time:

  • applying your quantitative and qualitative skills to large messy datasets to derive new insights;
  • building and implementing data tools to support our range of assurance work. For example, take a look at the data visualisations presented on our website: https://www.nao.org.uk/data-visualisations/;
  • collaborating with our financial auditors to review high value, high risk quantitative models which underpin accounting estimates. For example, the value of the student loans book, the rate of fraud and error in tax credit and benefit payments and the money needed in the future, to compensate people who have experienced clinical negligence.

Skills required

No previous experience of audit is necessary, and training will be provided in key Data Science skills such as R.

We do have some minimum criteria which you will need to meet:

  • 120 UCAS points from the 2017 tariff from your top 3 A Level grades (or equivalent) including Maths. General Studies does not count. If you have 104 UCAS points from the 2017 tariff (or equivalent) you may still be eligible to apply
  • Took an undergraduate degree course with a substantive quantitative component such as data science, operational research, mathematics, statistics, physics, engineering, management science, economics (the data science internship is unlikely to be suitable for people studying accounting finance degree courses), where:
  • You are in your second year of a sandwich degree course
  • You are in your final year and are expecting a 2.1 degree or better, or
  • You have completed your undergraduate degree course and achieved a 2.1 degree or better
  • You must be a UK, Commonwealth, EEA or Swiss national to comply with Civil Service nationality rules and must hold a valid work permit. We are not able to sponsor work visas.

Some previous programming experience is desirable but not essential

If you are interested in one of these vacancies, please submit your CV and application form, providing evidence of:

  • an example of where you used quantitative analysis to solve a problem (max 250 words)
  • an example of working in a team to complete a project to a challenging timescale (max 250 words)
  • Your interest and use of programming languages and/or visual analysis (max 250 words)

The deadline for applications is Sunday 1 December 2019 .

If you pass the initial application stage, we will invite you to complete a technical exercise followed by a telephone interview. This will then be followed by a final interview.

Remember to mention TARGETjobs when contacting employers!

More about this vacancy

Start date: 
September 2020
Region: 
London, North East
Number of vacancies: 
Up to 5
Benefits: 
Gym membership/subsidy, Pension scheme (with company contribution), Season ticket loan
Days' holiday: 
35
Degree requirements: 
Distinction, First, 2.1
Accepts applications from students / graduates requiring a work permit?: 
No
Degree subjects accepted: 
Chemical engineering & related, Civil engineering, construction & related, Economics & related, Electrical engineering & related, Environmental engineering & related, Information science, Manufacturing engineering & related, Maths & related, Mechanical engineering & related, Physics & related, Production engineering & related, Science & research
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