Coding as an engineering manager is an exercise in cognitive dissonance. If you’ve just become a manager, you’ve likely been measuring success by the quantity and quality of the code you ship as an individual contributor (IC). Suddenly, you have new metrics for success and your day-to-day work looks wildly different. One mentor tells you […]
All posts categorized in: Data Science
Insights from applying scientific methods and algorithms to Indeed data to help people get jobs.
D-Curve: An Improved Method for Defining Non-Contractual Churn with Type I and Type II Errors
Businesses need to know when customers end their business relationships, an act called “churn.” In a subscription business model, a customer churns by actively canceling their contract. The company can therefore detect and record this churn with absolute certainty. But when no explicit contract exists, churn is more passive and difficult to detect. Without any […]
Normalizing Resume Text in the Age of Ninjas, Rockstars, and Wizards
Left to right: Ninja by Mwangi Gatheca, Rockstar by Austin Neill and Magic by Pierrick Van Troost At Indeed we help people get jobs, which means understanding resumes and making them discoverable by the right employers. Understanding massive amounts of text is a tricky problem by itself. With source text as varied as resumes, the problem […]