Resume keywords for data analysts
The terms analytics postings repeat, grouped by where they belong on the page. The distinguishing feature of a strong analyst CV is not the tool list. It is whether any decision changed because of your work.
What data analysts postings actually ask for
Analyst adverts split cleanly in two. The first half is tools, and it is where filtering happens: SQL appears in almost every posting, and a CV without it is often gone before a human reads it. The second half is judgement, and it is where offers are decided: whether you can turn a question into a query, a query into a finding, and a finding into a decision somebody actually made. Most CVs cover the first half and skip the second.
The keywords, grouped
Grouped by the job each one does, because where a term belongs on the page matters as much as whether it is there at all.
| Group | Terms a posting uses | Why this group matters |
|---|---|---|
| Analysis and method | exploratory data analysis, A/B testing, hypothesis testing, statistical significance, cohort analysis, segmentation, forecasting, regression analysis, funnel analysis, data quality, data cleaning, root cause analysis | The half that separates an analyst from a dashboard operator. These belong in bullets, attached to a decision. |
| Tools and languages | SQL, Python, pandas, R, Excel, Tableau, Power BI, Looker, dbt, BigQuery, Snowflake, Redshift, Google Analytics (GA4), Jupyter | SQL is non negotiable and should appear early. Name the warehouse and the BI tool by product, because that is what the search looks for. |
| Business and communication | stakeholder management, requirements gathering, KPI definition, dashboard design, reporting automation, data storytelling, executive reporting, self-serve analytics, data governance | The terms that decide whether you are hired as a service desk or a partner. Every one of them needs a bullet behind it. |
| Certifications worth naming | Google Data Analytics Certificate, Microsoft Power BI (PL-300), Tableau Desktop Specialist, AWS Certified Data Analytics | Only if you hold them. Write the certificate name in full plus its code, because postings use both. |
| Verbs that carry evidence | quantified, modelled, forecast, automated, segmented, validated, reconciled, surfaced, recommended | Notice that none of them is 'analysed'. Analysis is the assumption, not the achievement. |
Where each group belongs on the page
Skills block: tools, languages, warehouse
SQL first, then the language, then the BI tool, then the warehouse. This block is read by a search before it is read by a person.
Bullets: method plus the decision it changed
cohort analysis and A/B testing only count where they end in an outcome. 'Ran the pricing test' is a task. 'Ran the pricing test that moved the team off the 20% discount' is analysis.
Bullets: the size of the data
Rows, tables, sources, refresh frequency, number of stakeholders served. Scale is the fastest way to show the difference between a spreadsheet and a warehouse.
Near the top: the certificate, if you are early career
For a first analyst role a named certificate does real work. Three years in, it belongs at the bottom.
A keyword only counts inside evidence
Both columns below contain the keyword. Only one of them survives a hiring manager reading it, which is the whole reason a keyword list is not a strategy on its own.
The second one names the decision that followed.
Skills: A/B testing, statistical significance, experimentation
Designed and read 14 pricing experiments, and killed a discount that testing showed cost 4% of margin for no measurable lift in conversion.
Automation is only interesting as time returned to somebody.
Automated reports for the sales and marketing teams.
Replaced 9 hand-built weekly spreadsheets with a dbt model and a Looker dashboard, returning roughly 6 hours a week to the commercial team.
How these terms appear in a real posting
Where these CVs lose points
- A tool list with no decision attached. Every analyst lists Tableau. Almost none says what changed because of a dashboard they built.
- 'Insights' as a noun with nothing after it. An insight nobody acted on is a slide. Name the action.
- No sense of scale. Rows, sources, refresh cadence, audience size. Without them a reader cannot tell a 200 row spreadsheet from a warehouse.
- Excel hidden out of embarrassment. Advanced Excel is still named in a large share of analyst postings. Keep it, and say advanced.
- SQL buried at the end of a long skills line. It is the term most likely to be searched. Put it first.
Check your CV against the posting in front of you
This page lists what data analysts postings tend to ask for. The advert you are answering today weights them differently, and that is the list that decides your application. Paste both into the checker at the top of this page to see which of its terms your CV never mentions, or read the worked Data Analyst CV example to see the terms sitting inside real bullets.
Get the gaps fixed, not just listed
Paste the job link and FitMyCV rewrites your CV and cover letter against that posting, keeping your real experience and your real numbers.
Data Analyst resume keywords: FAQ
Is SQL really the most important data analyst resume keyword?
It is the one most consistently present in analyst adverts, and the one most likely to be used as a hard filter. If you know SQL, it should be visible in the first third of your CV and evidenced in at least one bullet.
Should I list Excel on a data analyst resume?
Yes, and specify the level. 'Advanced Excel: Power Query, pivot tables, index match' is credible. Bare 'Excel' next to Python reads like padding.
Do I need a portfolio for a data analyst role?
It helps most when you are moving into analytics without an analytics job title. Link it once from the header. Do not let three tutorial projects sit above real work you did in a previous role.
How do I show impact when I only supported decisions?
Name the decision and your part in it honestly. 'Analysis behind the decision to close two regional depots' is strong and true. Claiming you closed them is neither.
Can I just copy these keywords onto my resume?
No, and a CV built that way falls apart in the first interview. Use the list as a checklist against work you have actually done. A term you cannot evidence in a bullet is a term that moves your rejection from the screen to the phone call, which is worse for you, not better.
How many keywords should a resume have?
There is no target number, and any tool that gives you one is guessing. What matters is coverage of the specific posting in front of you: the terms it repeats should be findable on your CV, in your own evidence. Twelve well placed terms beat forty in a list.
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