Data Analyst Apprentice in Cambridge

Data Analyst Apprentice in Cambridge

Cambridge Full-Time No home office possible
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At a Glance

  • Tasks: Support data analysis projects and create engaging visualisations to drive impactful research.
  • Company: RAND Europe, a not-for-profit organisation dedicated to evidence-based policy research.
  • Benefits: Gain hands-on experience, mentorship, and a recognised qualification while earning a competitive salary.
  • Why this job: Kickstart your career in data science with real-world projects that influence policy decisions.
  • Qualifications: Strong interest in data science; GCSEs in Maths and English; A-levels in relevant subjects.
  • Other info: Hybrid working model with excellent training and career development opportunities.

Please note that this is an apprenticeship position and therefore anyone with more than six months professional experience working as a data analyst or who holds a degree or Master’s degree in a subject such as Data Science, Business Analytics, Maths will not be eligible. You will also need to commit to completing a Level 4 Data Analyst Apprenticeship.

RAND Europe is a not-for-profit policy research organisation. Our mission is to help improve policy- and decision‑making through evidence-based research and analysis. We realise our mission by undertaking objective, balanced and relevant research, sharing the insights and information widely, and working in partnership with a range of clients and collaborators. Our work combines academic rigour with a task‑oriented approach. In addition to our strong ethos of evidence‑based research, RAND Europe is a values‑driven organisation.

This apprenticeship offers an excellent opportunity to gain hands‑on experience and develop practical skills in data science and analytics while working towards a recognised qualification. As a member of the Data Science Lab, you will support a range of research and data analysis projects, contributing to the development of high‑quality datasets, analytical tools, and insightful visualisations. This role enables you to learn from experienced data scientists, collaborate across multidisciplinary teams, and apply your skills to projects that inspire better policy and decision‑making. You will receive comprehensive training and mentorship, developing your expertise in data collection, cleaning, programming, and communication of data‑driven insights. Upon completion, you will have built a solid foundation in modern data science workflows and best practice within a research environment. As well as ensuring sufficient training to meet your Level 4 Data Analyst Apprenticeship, you will have access to a range of complimentary training services as part of RAND’s Data Science Lab.

Key responsibilities

  • Support the extraction, aggregation, and creation of datasets from a range of sources, including open databases, web scraping, policy documents, academic literature, and bibliometric data.
  • Clean, standardise, and prepare datasets from various sources, ensuring data quality and consistency prior to analysis.
  • Explore and analyse datasets using a range of analytical tools – including statistical methods, regression analysis, and machine learning techniques – to identify key trends and generate actionable insights for research projects.
  • Create clear, engaging data visualisations and dashboards to communicate key research insights to internal and external audiences, including policy makers.
  • Contribute to the adaptation of existing data workflows, such as the systematic application of large language models (LLMs) in a Python programming environment for data extraction and analysis.
  • Maintain up‑to‑date code repositories and documentation, ensuring code is well annotated and accessible for team use.
  • Assist in the development and upkeep of dashboards and digital observatories using tools such as Power BI, Streamlit, Shiny, Plotly or WordPress.
  • Collaborate across the Data Science Lab and research groups, providing support to colleagues and contributing to a positive, inclusive team environment.
  • Undertake ad hoc duties as required.

Skills and Experience

  • Strong interest in data science and research analytics, with demonstrable motivation to build a career in this field.
  • Familiarity with data analysis, statistical concepts, and creating data visualisations (coursework, science experiments, projects, or self‑study count).
  • Some experience with coding (e.g. Python, R, or similar) is desirable but not essential.
  • Excellent problem‑solving skills.
  • Effective verbal and written communication skills, with the ability to present findings clearly.
  • Strong team player who can work collaboratively and communicate clearly within a team.
  • Self‑starter with a positive attitude, curious mindset, and willingness to embrace new challenges.
  • Commitment to continuous learning and professional development.

Essential Qualifications

  • 7 GCSEs including Maths and English A* – B/5 – 93
  • A-levels (or equivalent) in Mathematics, Science, Computing or related subjects at grades A - C
  • Further experience or coursework in coding, statistics, or data analysis (desirable but not required).

Salary: ÂŁ21,000

Location: Cambridge, CB2 8BF. (Currently hybrid – spending three days per week in the office)

Rand Values

  • Quality. We pursue excellence. Apply the most rigorous standards to work. Take a holistic view of the problem‑solving landscape.
  • Objectivity. We are independent and impartial. Provide unbiased analysis and insights. Apply constructive, critical thinking to the challenges. Find and follow the best evidence wherever it leads.
  • Collaboration. We are stronger through the power of partnerships. Work as a team to achieve common goals, taking and sharing responsibility for success. Combine strengths and support one another. Value diversity, seek out and respect the contributions of others.
  • Service. We serve the public good and those with whom we work. Strive to have impact and make a difference to society and to clients. Honour your commitments to the organisation and others. Act with integrity.
  • Learning. We always look for better ways to do things. Use knowledge and insight to achieve better outcomes. Continuously improve and learn from experience. Combine curiosity with an entrepreneurial outlook.

By applying you are agreeing to Digital Native retaining your information, sharing this with potential employers and contacting you about apprenticeship opportunities that we feel you could be interested in.

Data Analyst Apprentice in Cambridge employer: Digital Native

RAND Europe is an exceptional employer, offering a unique apprenticeship opportunity in the heart of Cambridge. With a strong commitment to evidence-based research and a collaborative work culture, apprentices will benefit from comprehensive training, mentorship, and hands-on experience in data science, all while contributing to impactful policy-making. The inclusive environment fosters personal and professional growth, ensuring that every team member can thrive and make a meaningful difference.
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Contact Detail:

Digital Native Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Data Analyst Apprentice in Cambridge

✨Tip Number 1

Network like a pro! Reach out to people in the data science field, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on apprenticeship opportunities.

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your data analysis projects, even if they're from coursework or personal experiments. This will give you an edge when chatting with potential employers.

✨Tip Number 3

Prepare for interviews by practising common data-related questions. Brush up on your coding skills and be ready to discuss your thought process when tackling data problems. Confidence is key!

✨Tip Number 4

Don't forget to apply through our website! We’ve got loads of opportunities waiting for you, and applying directly can sometimes give you a better chance at landing that apprenticeship.

We think you need these skills to ace Data Analyst Apprentice in Cambridge

Data Analysis
Statistical Concepts
Data Visualisation
Python Programming
R Programming
Machine Learning Techniques
Problem-Solving Skills
Verbal Communication Skills
Written Communication Skills
Team Collaboration
Curiosity and Willingness to Learn
Data Cleaning and Preparation
Dashboard Development
Attention to Detail

Some tips for your application 🫡

Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Data Analyst Apprentice role. Highlight any relevant coursework, projects, or self-study that showcases your interest in data science and analytics.

Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to express your passion for data analysis and how you can contribute to RAND Europe's mission. Be genuine and let your personality come through.

Showcase Your Skills: If you've dabbled in coding or data visualisation, make sure to mention it! Even if it's just coursework or personal projects, showing your familiarity with tools like Python or R can set you apart from other candidates.

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, you’ll find all the details you need about the apprenticeship there!

How to prepare for a job interview at Digital Native

✨Know Your Data Basics

Brush up on your data analysis fundamentals. Make sure you can talk confidently about statistical concepts, data cleaning, and visualisation techniques. Even if you haven't had formal experience, be ready to discuss any relevant coursework or projects you've done.

✨Show Your Curiosity

Demonstrate your eagerness to learn and grow in the field of data science. Share examples of how you've tackled challenges or sought out new knowledge, whether through self-study or hands-on projects. This will show that you're a self-starter with a positive attitude.

✨Prepare for Technical Questions

While you may not need extensive coding experience, it's good to familiarise yourself with basic programming concepts, especially in Python or R. Be prepared to discuss any coding you've done, even if it's just for school projects or personal interest.

✨Communicate Clearly

Practice explaining complex data insights in simple terms. You might be asked to present findings or explain your thought process during the interview. Being able to communicate effectively is key, especially when working with multidisciplinary teams.

Data Analyst Apprentice in Cambridge
Digital Native
Location: Cambridge
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