Data analyst CV examples

This guide will walk you through creating a standout Data Analyst CV, from organising its structure and format to the best way of showcasing your technical expertise and professional achievements. By the time you’re done reading, you’ll write a CV that highlights your ability to deliver for companies.

Let’s put it this way: a well-structured CV is like a clean dataset. It’s way easier to process and it gets straight to the point. A clear, logical layout that’s nice and easy to navigate will help recruiters quickly understand why you’re the right person for the role.

Here’s how to structure your CV:

• Name and contact details – Position these at the very top so it’s easy for the recruiter to offer you the interview.
• CV profile – Begin with a concise summary of your expertise and professional accomplishments.
• Core skills – List your standout abilities, like data visualisation and SQL proficiency.
• Work experience – Detail your previous roles in reverse chronological order.
• Education – Include your academic qualifications and any certifications in data analytics or any related fields.
• Additional info – Optionally, mention personal projects or hobbies that show your genuine interest in the role.

First impressions count: a polished format ensures that your CV reflects your own professionalism. 

Recruiters are looking for information they can quickly digest, so keep it clean and reader-friendly. They’ve just sifted through a hundred applicants – make your one a more pleasant read than the competition.

Always stick to these formatting principles:

• Bullet points – Break information into manageable chunks for easy skimming.
• Divide sections – Use clear headings to make navigation less of a hassle.
• Use an appropriate font – Prioritise your CV’s readability with clean, professional design choices.
• No more than 2 pages – This gives you plenty of space to share your story (without making it a novel…)

Your profile is your CV’s headline – a brief overview that hooks the recruiter and sets the stage for your experience and skills. For a Data Analyst, this section should emphasise your technical expertise and ability to solve data-related problems.

Build your CV now 

What’s the key to a winning professional profile? Relevance. Tailor your profile to reflect the job description, ensuring it aligns with the role’s requirements as conveniently stated in the job advert you’re replying to. Those are, after all, the things a company wants.

Here’s the things your profile should include:

• Where you worked – Mention industries or companies whose data you’ve worked with, such as finance, healthcare, or e-commerce.
• Your top qualifications – Include any degrees, certifications, and any relevant training.
• Technical expertise – Note the skills like SQL or Power BI which you know will come in handy for a data analytics role.
• People you’ve worked with – Say which departments or teams you supported with your data analysis.
• Types of data you’ve worked with – Specify whether you’re trained to handle customer data, or financial figures, and so on.
• Methodologies you know – Highlight analytic techniques like predictive modeling, regression analysis, or clustering algorithms to show depth in data handling.
• Relevant tools you’ve used – Make sure you tailor these to reflect your familiarity with the industry relevant to the role!

The core skills section is a snapshot of your technical toolkit. In a column or two, you want them to give a recruiter an immediate sense of what you’re going to bring to the table once you’re hired.

This section is super flexible, and you can change or add core skills depending on what role you’re looking at. 

Avoid the mistake of broad phrases that might apply to any job: instead of saying you “know Excel,” say you’ve built pivot tables and automated reports – it’ll really prove that you know your stuff.

Just like data analysis, employers will want you to apply your analytic skills to the real-world: so proven experience in a professional environment is key.

List your roles in reverse chronological order, focusing on how your contributions added value to your previous employers. Bullet points will make your accomplishments easier to digest. And if you’re newer to the field, highlight relevant academic projects or internships, along with any freelance work you might’ve done.

• Outline – Share the type of company and its name, your role within it, and the context of your work – what did you do there?
• Responsibilities – Highlight key tasks you performed and how doing them brought value to the organisation.
• Achievements – Showcase measurable outcomes, focusing on the results you delivered or improvements you made. Lucky for you, data and figures make this section look really impressive.

The education section is where you show the foundation of your analytical skills. List your degrees, certifications, and relevant training – they’ll all help prove that you’re serious about this role in particular.

New to the field? Go into more depth about any coursework or academic projects that hopefully demonstrate your expertise. Experienced? Keep it brief – recruiters prefer experience anyway.

As always, put the qualifications you earned most recently towards the top, and your GCSEs at the bottom.