What do recruiters look for in a fresher data analyst resume?
Without work experience, a recruiter scanning your resume is asking three questions: does this person have the tools the job post lists, have they used them on something real, and can they communicate clearly? Every section should help answer one of those.
In practice that means:
- Keywords that match the job post, such as SQL, Excel, Power BI or Tableau, Python and statistics, so applicant tracking systems (ATS) and recruiters can see the fit quickly.
- Projects written as results, with a business question, the tools used and a finding.
- Clean, readable formatting: one page, one column, consistent dates and no spelling errors. For an analyst, sloppy formatting reads as sloppy work.
What format and length should a data analyst resume be?
| Element | Recommendation for freshers |
|---|---|
| Length | One page |
| Layout | Single column; no tables, text boxes or graphics for key information |
| Font | A standard font such as Calibri, Arial or Garamond at 10–12 pt |
| File type | PDF, unless the portal asks for Word |
| File name | FirstName-LastName-Data-Analyst-Resume.pdf |
| Photo, date of birth, marital status | Leave them out unless an employer specifically asks |
| Section order | Header, summary, skills, projects, education, experience or internships, certifications |
If you have a relevant internship, move Experience above Projects. Otherwise, projects are your experience and belong near the top.
How to write each section of a data analyst resume
Header
Name, city, phone, a professional email, and three links: LinkedIn, GitHub and a portfolio or dashboard link (Tableau Public, a published Power BI report or a simple portfolio page). Check every link opens without a login.
Summary (2–3 lines)
Skip generic objectives such as "seeking a challenging role". Say what you can do and the evidence:
Weak: Hard-working graduate looking for an opportunity to grow in data analytics.
Stronger: Commerce graduate with hands-on SQL, Excel and Power BI. Built three end-to-end analysis projects on public retail and delivery data, including a cohort retention dashboard. Looking for an entry-level data analyst role in Pune or remote.
Skills
Group skills so they are easy to scan, and only list what you could use in a live test:
- Languages and querying: SQL (PostgreSQL: joins, CTEs, window functions), Python (pandas, matplotlib)
- Spreadsheets: Excel (PivotTables, XLOOKUP, SUMIFS, Power Query), Google Sheets
- BI: Power BI (DAX measures, data modelling) or Tableau
- Analysis: descriptive statistics, A/B test basics, cohort and funnel analysis
Avoid skill bars and star ratings. "Python ★★★★☆" tells a recruiter nothing and wastes space.
Projects (the most important section)
Include two or three projects. Give each a title, the tools, a link, and two or three result bullets. Choose projects that together cover the job post's tools. Our guide to data analyst resume projects explains how to pick them.
Education
Degree, college, city, years, and your score if it helps. Add relevant coursework (statistics, econometrics, databases) only if it supports the role.
Experience and internships
Any role counts if you describe the analytical part: a sales internship where you built the weekly report, a college fest where you tracked registrations, or family business accounts you moved from paper to Excel. Write them with the same bullet formula as projects.
Certifications
List a few relevant ones with the issuer and year. A certificate supports your skills line; it does not replace projects. See our guide to free data analytics courses with certificates for what each one proves.
How do you write resume bullet points as a fresher?
Use this formula for every bullet:
Action verb + what you analysed + tool or method + result or finding (with a number)
The result can be a business finding ("found that…"), a scale ("across 50,000 orders") or an efficiency gain ("cut report time from 3 hours to 20 minutes"). The examples below use illustrative numbers; always use the real figures from your own work.
| Weak (task) | Strong (result) |
|---|---|
| Worked on SQL queries for an e-commerce dataset | Wrote SQL cohort queries (CTEs, window functions) on 50,000 orders to find that 22% of first-time customers reordered within 30 days |
| Made a Power BI dashboard | Built a Power BI sales dashboard with 12 DAX measures, including YoY growth and margin, used to compare 4 regions in one view |
| Cleaned data using Python | Cleaned a 30,000-row ride dataset in pandas, removing 1,200 duplicate trips and standardising 40 location labels before analysis |
| Did Excel work during internship | Automated a weekly sales report with Power Query and PivotTables, reducing preparation time from about 3 hours to 20 minutes |
| Analysed A/B test data | Evaluated a checkout A/B test (4,800 users) and recommended extending it, as the 25% lift was not significant at the 5% level |
Good action verbs for analysts: analysed, built, cleaned, automated, modelled, segmented, forecast, identified, reduced, presented.
Need projects worth putting on your resume?
Resume bullets are only as strong as the work behind them. The ISS Data & Business Intelligence program ends in a portfolio capstone, and its career support includes resume, LinkedIn and portfolio review and mock interviews; ISS does not guarantee jobs or placement. You can also start with the free Data Analyst Starter Kit on this page, which includes five project briefs.
View Data & Business Intelligence curriculum →Sample data analyst resume for a fresher
This is a template, not a real person. Replace every bracketed field, and swap the illustrative numbers for the real results of your own projects.
[Your Name]
[City] | [phone] | [email] | linkedin.com/in/[handle] | github.com/[handle] | [portfolio link]
Summary
[Degree] graduate with hands-on SQL, Excel, Power BI and Python. Built three end-to-end analysis projects on public retail, delivery and survey data, including a cohort retention dashboard. Seeking an entry-level data analyst role.
Skills
SQL (PostgreSQL: joins, CTEs, window functions) | Excel (PivotTables, XLOOKUP, SUMIFS, Power Query) | Power BI (DAX, data modelling) | Python (pandas, matplotlib) | Statistics (descriptive, A/B test basics) | Cohort and funnel analysis
Projects
E-commerce customer retention analysis | SQL, Power BI | [link]
- Wrote SQL cohort queries on [50,000] orders from a public e-commerce dataset to measure 30, 60 and 90-day repeat purchase rates.
- Found that customers whose first order was in [Home] reordered at [2x] the rate of [Electronics] buyers, and recommended a targeted second-order offer.
- Built a one-page Power BI dashboard with cohort heatmap, YoY revenue and category filters for a category-manager audience.
Food delivery time analysis | Python (pandas) | [link]
- Cleaned [30,000] delivery records in pandas, removing [1,200] duplicates and standardising [40] area names.
- Showed that median delivery time rose [18%] during evening peak hours, driven mostly by [3] areas, using grouped medians rather than means because of skew.
Sales reporting automation | Excel, Power Query | [link]
- Rebuilt a monthly sales report so a new export refreshes all PivotTables and charts in one click, cutting preparation time from about [3 hours] to [20 minutes].
Education
[Degree], [College], [City] | [Year]–[Year] | [Score, if strong]
Relevant coursework: [Statistics], [Business Mathematics], [Database Systems]
Experience
[Sales Operations Intern], [Company], [City] | [Month Year]–[Month Year]
- Maintained the weekly dealer sales tracker in Excel and flagged [5] dealers with falling orders for follow-up by the sales team.
Certifications
[Certificate name], [Issuer], [Year]
How do you make a data analyst resume ATS-friendly?
An applicant tracking system stores applications and lets recruiters search and filter them. Different systems parse resumes differently, so the safe approach is to make yours easy for any system and any human to read:
- Use standard section headings: Summary, Skills, Projects, Education, Experience, Certifications.
- Keep key information in plain text, not in tables, text boxes, headers, footers, icons or images.
- Mirror the job post's wording. If it says "Power BI" and "SQL", use those exact terms, not only "BI tools" or "databases".
- Spell out and abbreviate once where it helps: "Exploratory data analysis (EDA)".
- Use a text-based PDF exported from Word or Google Docs, not a scanned image. Test it by selecting and copying the text.
- Never stuff keywords in white text or long lists. Recruiters read the resume after the search, and it looks dishonest.
How do you tailor your resume to each job?
Keep one master resume with every project and bullet, then make a short version for each application. It takes about 15 minutes:
- Copy the job post and highlight the tools and tasks it repeats.
- Make sure each highlighted tool appears in your skills line if you can genuinely use it.
- Reorder projects so the most relevant one is first.
- Adjust your summary's last line to name the role type, such as "product analyst" or "business analyst".
For example, a post that mentions "SQL, Tableau, stakeholder reporting" should see your SQL-heavy project first and a line about presenting findings. If you are unsure which role you are aiming for, our comparison of data analyst vs business analyst can help.
What mistakes should freshers avoid on a data analyst resume?
| Mistake | Why it hurts | Fix |
|---|---|---|
| Listing tools you cannot use in a test | SQL and Excel are often tested live; gaps show immediately | List only what you could demonstrate tomorrow |
| Course names as projects ("Capstone 1") | Says nothing about the question or result | Title projects by the business problem |
| Bullets that describe tasks | Every applicant "worked on dashboards" | Use the action + data + tool + result formula |
| Numbers you cannot explain | Interviewers ask how you got every figure | Keep a notes file for each project |
| Broken or private links | The recruiter cannot see your work | Open every link in a private browser window |
| Two-page resume padded with school details | Hides the relevant parts | Cut to one page; drop Class 10 details if you have a degree |
| Typos and inconsistent dates | Signals poor attention to detail, a core analyst trait | Proofread aloud and ask someone else to check |
Final checklist before you apply
- One page, single column, text-based PDF.
- Skills line matches the job post and you can back every item.
- Two or three projects, each with a link and at least one result.
- Every bullet starts with an action verb and most include a number.
- All links work without a login.
- You can explain every number in an interview. Practise with our data analytics interview questions.
Frequently Asked Questions
How long should a data analyst resume be for a fresher?
One page. Recruiters scan quickly, and a fresher rarely has enough relevant material to fill two pages without padding. Cut school details and unrelated activities first.
What should a fresher put on a data analyst resume with no experience?
Two or three projects on public data, written as results, plus a clear skills line, education and any internship or part-time work described in terms of the analysis you did. Projects stand in for work experience.
Which skills should I list on a data analyst resume?
List the skills the job post asks for that you can genuinely use: usually SQL, Excel, one BI tool such as Power BI or Tableau, Python with pandas, and basic statistics. Group them and avoid star ratings.
Should I include certificates on my data analyst resume?
Yes, a few relevant ones with the issuer and year. They support your skills section, but they do not replace projects, because interviews test what you can do.
Is a resume template with two columns and icons bad for ATS?
It can be. Some applicant tracking systems read multi-column layouts, tables and icons out of order. A simple single-column layout with standard headings is the safest choice.
Should I put my photo on a data analyst resume in India?
It is not needed for most private-sector analyst roles. Leave out the photo, date of birth and marital status unless an employer specifically asks for them.
Sources and methodology
This guide is ISS editorial guidance on resume structure and writing for fresher data analyst roles, reviewed in September 2026. It contains no salary, hiring-rate or job-count figures.
- The sample resume is a fictional template. It does not describe a real person or an ISS learner, and every number in it is a placeholder.
- The bullet examples use illustrative figures. Some mirror the worked examples in our data analyst skills guide (the A/B test) and pandas crash course (cleaning steps).
- ATS advice is general. Applicant tracking systems differ in how they parse files, so check any instructions on the employer's application page.
- ISS: Data & Business Intelligence program page (portfolio capstone and career support).
Next steps
Pick your two strongest projects, rewrite every bullet with the formula above, and test the finished PDF by copying its text into a plain document. Then tailor it for each application.
If you need stronger projects first, the Data & Business Intelligence curriculum ends in a portfolio capstone, with resume and portfolio reviews as part of career support (no job guarantee). Applying is free: apply here. The free Data Analyst Starter Kit on this page has five project briefs to get you started.