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 […]

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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 […]

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Time-Tested: 7 Ways to Improve Velocity When A/B Testing a New UX

A/B testing holistic redesigns can be tough. Here at Indeed, we learned this firsthand when we tried to take our UX from this to this: The Indeed mobile Search Engine Results Page (SERP) circa mid-2017 (left) and circa mid-2018 (right) Things didn’t go so hot. We’d spent months and months coming up with a beautiful […]

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