Why you should listen to me.

I came into data without a math or software background and taught myself the work, so I was a career changer before I was anything else. Since then I have worked as both an individual contributor and a manager, building teams from the ground up to more than ten people spanning new grad through senior staff.

On the hiring side I have screened resumes and run interviews across most of the levels I hire for, and I designed those loops rather than only sitting on them. I also interview regularly myself, which keeps my read on the market current rather than five years out of date. That has produced offers at Meta (L6), Coinbase (L5), and Airbnb (M1). When I tell you what a rubric rewards, it is because I have written one and been scored against one in the same year.

This began as mentoring junior colleagues and friends, where the same few failures kept appearing: resumes that listed assignments rather than impact, no credible answer on where AI fits into daily work, memorized SQL with no framework for a case study, one rehearsed project delivered to every cross-functional audience, and offers accepted at the first number. I have made most of those mistakes myself. The fix is rarely to prepare harder across the board. It is to find the specific thing costing you interviews and work on that.