Clarifying what data roles actually mean.
A smarter way to search data jobs. By what you'll actually do, not just what the title says.
The problem
A “Data Analyst” at one company builds dashboards. At another, they're writing production ETL pipelines. Same title, completely different jobs.
And then there are the creative interpretations: “Data Ninja,” “Analytics Rockstar,” “Chief Data Evangelist.” What do these people actually do?
The same title means wildly different things at different companies. Is a “Data Scientist” doing ML research or building dashboards? It depends who's hiring.
“Growth Hacker.” “Insight Wizard.” “Data Storyteller.” Whimsical titles make it impossible to compare roles or know what you're signing up for.
Our approach
- 01Data normalization
We aggregate job postings from across the industry, standardizing the wild variety of titles and descriptions into a consistent format that enables meaningful comparison.
- 02Classification algorithm
A hybrid rule-based + Claude Haiku classifier analyzes job descriptions to categorize roles by what you'll actually do. Not by what the title claims.
- 03Clear categories
Every job is classified: Analyst, Data Engineer, Data Scientist, Analytics Engineer, ML Engineer, Data Leadership, and Other — based on the actual work involved.