You're going for a Data Analyst role.
And we're rooting for you.
But does your experience match the job?
Here's what the role really asks for, and a clear way to see where you stand before you apply.
The core of the role
Four things a Data Analyst is really hired to do.
Most Data Analyst “skills” lists are just a pile of tools. These are grouped the way the work actually flows, from cleaning raw data to turning it into a decision someone can act on.
Turn raw data into clean data
Most of the job lives here: taking messy, incomplete data and getting it to a state you can actually trust before you draw a single conclusion.
Find the signal
You use statistics, not gut feel, to work out what the numbers are actually saying and what's just noise.
Work the data stack
You pull the data you need from where it lives and keep it organised, so your analysis is repeatable instead of a one-off scramble.
Make it useful, keep it safe
A finding nobody understands changes nothing. You turn analysis into clear visuals and decisions, and you handle sensitive data responsibly.
Skills grounded in ESCO occupation data (European Commission) for Data Analyst, an exact match, then translated into plain language.
See where you stand
You're aiming for a Data Analyst role. How close are you?
Drop your CV, add the job you're targeting, and get an honest match in about 30 seconds. Free, no account, and your CV carries over so you never upload it twice.
A solid partial match. Your cleaning and querying experience lands well; the statistics and stakeholder-facing side is worth strengthening before you apply.
Straight answers
Data Analyst questions people usually ask.
What skills do you need to be a Data Analyst?
The backbone is four things: getting messy data clean and trustworthy, analysing it with statistics rather than guesswork, working the data stack (SQL above all), and turning the result into something people can act on. Most job ads rename these, but that's what they're testing for.
Do you need to know how to code to be a Data Analyst?
SQL, almost always. Python or R, often, but not everywhere. You're not expected to write software; you're expected to query, clean, and analyse. Plenty of strong analysts work mostly in SQL, Excel, and a BI tool.
What's the difference between a Data Analyst and a Data Scientist?
Roughly: a Data Analyst explains what happened and why, using existing data and statistics; a Data Scientist builds models to predict what happens next. The lines blur constantly, so read the actual job description rather than the title.
How do I show Data Analyst skills on my CV?
Lead with the decision your analysis drove, not the tool. “Built a dashboard” says little; “built a churn dashboard that flagged at-risk accounts and cut churn by 12%” shows the skill working. That's exactly what our scan helps you pull out of your own history.
This application incorporates information from ESCO (European Skills, Competences, Qualifications and Occupations), © European Union, used under the ESCO terms of use.
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