GitHub profile README for data analysts: a template to copy

Recruiters for analyst roles rarely read code in depth. They click the GitHub link on your resume, see the profile page for a few seconds, and maybe open one project. The profile README decides what they see in those seconds.

Create the special repository

1. 1Sign in to GitHub and create a new repository.
2. 2Name it exactly your username. If your username is anjali-mehta-example, the repository is anjali-mehta-example. GitHub shows a note confirming it is a special repository when the names match.
3. 3Make it public and tick "Add a README file".
4. 4Edit README.md and commit. The content appears on your profile page.

GitHub's own documentation describes this under "Managing your profile README" in GitHub Docs if the interface has changed.

The template

Keep it plain. Heavy badge walls, animated banners and visitor counters distract from the work and add nothing an analyst hiring manager needs.

# Anjali Mehta

Data analyst working with SQL, Excel and Power BI. I like turning messy
operational data into a short answer someone can act on.

## Projects

| Project | Question it answers | Tools |
|---|---|---|
| [Returns analysis](https://github.com/anjali-mehta-example/returns-analysis) | Which categories and pincodes drive returns? | MySQL, Power BI |
| [Sales MIS rebuild](https://github.com/anjali-mehta-example/sales-mis) | Can a monthly report refresh without copy-paste? | Excel, Power Query |
| [Delivery time SQL](https://github.com/anjali-mehta-example/delivery-sql) | How do delivery-time percentiles vary by area? | SQLite |

All project data is synthetic and generated by scripts in each repository.

## Tools

SQL (MySQL, SQLite) · Excel (Power Query, pivots, XLOOKUP) · Power BI (DAX,
star schema) · Python (pandas basics)

## Contact

anjali.mehta.example@email.com · linkedin.com/in/anjali-mehta-example
Based in Noida, open to NCR and remote roles.

Why each part is there

• Two-sentence intro: role, tools, and a hint of how you think. Nothing about passion or journeys.
• Project table: the "question it answers" column is the most important. It shows that each repository exists to answer something, not to practise syntax.
• Synthetic data note: stated once, visibly, so no one wonders whether you exposed an employer's data.
• Contact line: removes a step for anyone interested.

Pin the same three repositories

Below the README, GitHub lets you pin up to six repositories. Pin the three from your table, in the same order, so the profile tells one story. Unpin tutorial forks and course exercises; they are fine to keep, just not in the pinned slots.

Each pinned repository needs its own README

A profile README that links to empty repositories does more harm than having none. Each project README should cover:

• The question and why it matters
• Where the data comes from (synthetic generation script, or public source with licence)
• How to run it, in three or four commands
• The main findings with one table or chart
• Limitations

The existing article on writing a project README an interviewer can verify covers this in detail; this piece is only about the profile page.

Clean-up before you add the link to your resume

If you ever committed a secret, deleting the file in a new commit is not enough, because it stays in history. Revoke or rotate the credential first.

Keep it current with one rule

Whenever you finish a project that is better than one in your table, replace the weakest row. Three strong projects are enough. Link the profile from your resume and LinkedIn, as shown in the annotated fresher resume, and decide separately whether you also need a site, using the portfolio website decision guide. Projects built in the Data Analyst programme are designed to fill exactly this kind of table.