ARU Winter Internship : Data & Evaluations Intern (quantitative analyst and mixed-methods)
ARU Temps
Sourced from ARU Temps's careers site · verified 12 hours ago
The intern will receive appropriate information-governance training and guidance on responsible data handling and will work only with data they are authorised to access. Access to identifiable health data is not a requirement of the internship.
The intern will:
- Collect, organise, clean and check datasets, flagging missing, inconsistent or duplicate information.
- Support exploratory and descriptive analysis of health and care data, identifying patterns and trends under supervision.
- Create tables, charts and visualisations, and help prepare clear summaries, reports and presentations.
- Assist with evidence reviews under the guidance of the team, document analytical methods and help prepare evaluation outputs.
- Maintain accurate records of data sources, analysis steps and outputs, handling information confidentially.
- Develop analytical skills and suggest improvements to the accuracy and clarity of analysis and reporting.
Required skills/qualifications
ARU UG student - currently studying a relevant university degree. This role is particularly suited to final-year students, or students in earlier years who can demonstrate advanced analytical skills and the ability to work independently on agreed tasks.
- A good understanding of data analysis and confidence using spreadsheets to organise and summarise information.
- Good numeracy, analytical thinking and attention to detail, with the ability to identify patterns and communicate findings clearly.
- Curious, methodical and willing to learn; able to work independently on agreed tasks and collaboratively with the team, follow guidance, seek support when needed and handle data responsibly and confidentially.
- Desirable: an interest in health and care data, research or evaluation; familiarity with one analytical tool, such as R, Python, SQL, Power BI or similar (experience with all is not expected); or experience analysing and presenting data in a university project.
Learning outcomes
At the end of the internship the student will be able to demonstrate:
- Practical skills in preparing, cleaning and checking health and care datasets, with clear records of data sources and analysis steps.
- The ability to carry out exploratory and descriptive analysis under supervision, identify patterns, recognise limitations in the data and present findings through clear charts, summaries and reports.
- Experience contributing to evaluation projects, working collaboratively, handling information confidentially and using supervision and feedback to develop their skills.
How to apply: Please click on the 'apply' button ensuring your CV is attached along with a cover letter which showcases your relevant skills and experience for the role.
Skills
- ARU undergraduate student
- relevant university degree
- data analysis
- spreadsheets
- numeracy
- analytical thinking
- attention to detail
- pattern identification
- communication
- independent work
- team collaboration
- follow guidance
- responsible data handling
- confidentiality
- health and care data
- research
- evaluation
- R
- Python
- SQL
- Power BI
- data presentation
- healthcare data
- quantitative analysis
- mixed methods
Summary
Prepare and analyze health and care datasets, support evaluation projects, and communicate findings through charts, reports, and presentations.
Job title
Data & Evaluations Intern (quantitative analyst and mixed-methods)
Experience level
internship; student role
Industry
healthcare
Location
Cambridge, UK · On-site
+ 1 more location
- On-site
As listed by the employer.
Salary
£13.45
Listed in the job description
Management role
No
- Nov 5, 2026 First posted
- Nov 5, 2026 Live now
As observed on the employer's careers site by ApplyAll. We show every change we've seen including removals.
Posting history
- Nov 5, 2026 First posted
- Nov 5, 2026 Live now
As observed on the employer's careers site by ApplyAll. We show every change we've seen including removals.
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