Guides

Guides for data, AI and analytics careers
Practical, specific, no filler.

Short guides on the parts of a resume and an interview that data professionals find hardest, each with worked examples you can adapt.

All guides

Start with the one that is closest to your next step

Each guide stands on its own. Examples are illustrative, not taken from any real candidate.

What interviewers listen for, a five-part structure you can reuse, a worked example and the mistakes that sink a good story.

Round figures read as guesses. Six kinds of number you can defend, where each one lives, and what to write when you cannot find the exact figure.

Ownership is not a verb. It is a decision and what came after it. Four signs to write down, a rewrite recipe and the follow-up questions to expect.

By role

These guides apply across data roles. For what we see in real resumes for each one, see where each role loses out.

Data engineers, data scientists and AI and ML engineers each lose out in different places. See where each role loses out or compare graph with other resume tools.

Start with your resume. graph shows you what it understood and what is missing.

Start with your resume*Free to start, no credit card required