How to Get a Data Analytics Job With No Experience
Breaking into data analytics without formal experience is possible if you focus on the right skills, build proof through projects, and position yourself clearly to employers. This guide explains what hiring managers look for and how to make yourself a credible candidate in a competitive UK job market.
Yes, you can get a data analytics job with no experience. I want to say that from the start, because a lot of people assume they need years of office experience or a perfect CV before they can even apply, when the reality is you don’t.
What you do need is a better plan than simply sending out applications and hoping somebody takes a chance on you. In data analytics, employers are usually looking for evidence. That evidence can come from projects, training, certifications, portfolios, and practical exercises, not just past job titles.
If you haven’t already, it’s also worth reading our guide on how to get a job with no experience, which covers the bigger picture. In this guide, I’ll walk you through how to build relevant skills, create proof of your ability, and make yourself genuinely employable in a competitive UK market.
Written by
With four years at Learning People and a solid foundation in IT and Cybersecurity, Chris guides people through the fast-evolving tech landscape and into their dream jobs. He combines hands-on technical expertise with insider industry insights to help learners make informed career decisions.
What's on this page?
Jump to:
- What Employers Actually Look for in Entry-Level Data Analysts
- Build Proof of Your Skills Before You Apply
- Hidden Analytics Experience You May Already Have
- Build a Portfolio Before You Apply for Data Analytics Jobs
- Tailor Your CV and LinkedIn Profile for Data Analytics Roles
- Apply Strategically Instead of Sending Dozens of Generic Applications
- Can Certifications Help You Get Hired Faster?
- Final Thoughts: The Best Way To Start A Career In Data Analytics
- How to Get a Data Analytics Job With No Experience FAQs
What Employers Actually Look for in Entry-Level Data Analysts
At entry-level, employers usually are not fixated on job titles. Employers want to see that you can work with data, solve problems, and explain what your findings mean in a clear and useful way. That’s a really important distinction. Having no formal experience is one thing. Having no evidence is another.
I’ve seen plenty of candidates rule themselves out too early because they have never held the title of Data Analyst. But in most cases, hiring managers are asking a simpler question: can you take complex information, make sense of it, and explain what matters?
For a junior role, we’d usually expect to see:
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Spreadsheet confidence so you can sort, filter, clean, and analyse data accurately
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SQL (Structured Query Language) basics to search for, organise, and analyse data stored in databases
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Data visualisation skills using tools like Excel, Power BI, or Tableau
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Analytical thinking so you can spot patterns, trends, and anomalies
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Clear communication, because insight only matters if you can explain it well
In the UK market, commercial awareness also helps. Employers want Junior Data Analysts who understand that data is there to support decisions, improve performance, and solve business problems, not just produce charts for the sake of it.
Build Proof of Your Skills Before You Apply
The goal is not to master every tool or process straight away. It is to build enough confidence to complete projects, explain your thinking, and show employers that you can solve real problems with data.
If you want a more structured way to build that foundation, our Data Analytics courses are designed to help you build job-ready knowledge step by step.
Proof can come from a few different places, including:
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Course projects that show you can clean data, spot patterns, and present findings clearly
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Portfolio projects, including self-directed case studies built from public datasets, where you explain the question, your approach, and what you found
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Freelance tasks for individuals or small businesses that need help with spreadsheets, reporting, or dashboards
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Reporting tasks in your current role, even if your job title is not Data Analyst
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Internships that give you exposure to real business data and team workflows
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Volunteering for a charity, local group, or community organisation that could use support with data or admin reporting
Fact: Demand for Data Professionals in the UK Increased by Around 25%
Recent labour market analysis shows that employer demand for data analysts and data scientists in the UK has increased by around 25% in recent years, as organisations rely more heavily on data to guide business decisions.
For people trying to enter the field, this growing demand means companies are actively looking for people who can analyse data and generate insights.
Build a Portfolio Before You Apply for Data Analytics Jobs
If you have no work experience, your portfolio does part of the talking for you. It gives employers something concrete to look at before they ever meet you. That matters because a CV can only say so much.
A good portfolio shows how you think, how you approach a problem, and how you turn data into something useful.
For a beginner, it does not need to be huge. In fact, I’d rather see two or three well-explained projects than a long list of rushed ones. Quality carries far more weight than quantity here.
Strong starter portfolio projects might include:
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A sales dashboard showing trends, top products, or regional performance
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Survey insights that turn responses into clear findings and actions
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A marketing campaign data review looking at clicks, conversions, or return on spend
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A public dataset case study based on an open-source dataset you found and analysed yourself
You can present these on:
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GitHub if you want to show your files, project steps, and documentation
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Tableau Public if you want employers to view interactive dashboards you have published online
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Power BI if your work is focused on report building and visual analysis
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A simple personal site if you want one place to showcase your portfolio more neatly
What makes a portfolio project stand out?
The strongest projects are easy to follow. I’d include:
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The business question
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The dataset
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The method
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The findings
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A clear recommendation
That last point is very important. Employers are not just looking for screenshots or charts. They want to see whether you can explain what the data means and what someone should do next.
Fact: Data Analytics Is One of the Most In-Demand Digital Skills in the UK
Industry hiring research consistently lists data analytics among the most in-demand digital skills in the UK job market, alongside artificial intelligence and data engineering capabilities.
This demand highlights how valuable analytical skills have become across industries. For people looking to break into data analytics, learning tools like Excel, SQL, and data visualisation platforms can make you far more competitive when applying for entry-level roles.
Tailor Your CV and LinkedIn Profile for Data Analytics Roles
Once you have some evidence of your skills, the next step is positioning. This is where a lot of strong candidates undersell themselves. If you are changing fields, your CV and LinkedIn profile need to make that move feel clear and intentional.
Start with your headline or profile section. I’d make this specific to data analytics rather than leaving it broad or tied to your previous field. Your skills section should also reflect the tools and tasks employers are actually hiring for, especially if they appear repeatedly in job descriptions.
It also helps to bring in project-based evidence and measurable outcomes, such as the examples mentioned above.
I’d also use the same language employers use. Relevant keywords from job descriptions can help your profile feel aligned with the role without sounding forced. And if you are building credibility through training, our article on why employers are prioritising certified data and AI talent gives useful context.
How to describe yourself if you have never held a Data Analyst title
You do not need to pretend you already are something you are not. But you also do not need to undersell yourself. A better approach is to describe yourself in a way that is honest and forward-looking.
For example, you might position yourself as a career changer building practical skills in data analytics, or someone with experience in another field who now has hands-on experience in reporting, dashboards, data analysis, and insight generation.
The key is to connect your past work to where you are going next.
Apply Strategically Instead of Sending Dozens of Generic Applications
More applications do not always lead to better results. I’d rather see a few well-targeted applications than 40 rushed ones.
Focus on roles such as:
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Junior Data Analyst
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Reporting Analyst
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BI Analyst
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Data Technician
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Operations Analyst
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Marketing/Data Assistant positions that involve data.
Do not rule yourself out just because you do not match every line of the job description. If you meet many of the core requirements, it is still worth applying.
Can Certifications Help You Get Hired Faster?
Certifications can help, especially if you are changing careers and need a clearer way to show commitment, structure, and up-to-date skills.
That said, a certification on its own is not enough. It will not replace proof that you can actually use the skills. Employers still want to see projects, practical ability, and a basic understanding of how data supports business decisions.
Where certifications really help is by reducing guesswork. A structured learning path can show you what to learn, in what order, and how the pieces fit together. That often builds confidence as well as knowledge. If you are mapping out your next steps, our guide on how to become a Data Analyst is a useful place to start.
Hear from data student, Ashton
Ashton enrolled on the Data Analyst Pathway with Learning People while transitioning from a non-IT and non-data background. Enrolling with Learning People has given Ashton a clear sense of direction, and the confidence to pursue her dream role in data analytics.
Final Thoughts: The Best Way To Start A Career In Data Analytics
If you’re thinking about moving into data analytics, it’s normal to feel unsure at the beginning. I see that hesitation quite often. Many people assume they need to feel completely ready before taking the first step.
In reality, you do not need years of experience to get started. What matters is learning the core skills, building evidence of what you can do, and showing genuine curiosity about how data supports better decisions.
If you’d like guidance on your next steps, you can book a free career consultation with one of our Consultants. We’re here to help you plan a realistic path into a Data Analyst role.
How to Get a Data Analytics Job With No Experience FAQs
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