Millennial job seekers in the U.S. and Canada are editing their résumés to remove age-revealing details in a practice dubbed “resume Botox” [1, 2, 3].

This trend highlights growing concerns over age discrimination in a tightening white-collar job market. By hiding their age, candidates hope to avoid being dismissed as overqualified or too old for specific roles [1, 4].

Applicants typically target details such as graduation dates or early career milestones. Some millennials are removing up to 10 years of professional experience from their documents to appear younger [4]. This strategy aims to increase the likelihood of receiving callbacks from recruiters who may hold subconscious biases against older workers [1, 2].

Data from Canada indicates a significant portion of the workforce feels this pressure. Approximately 28% of Canadians have downplayed their work experience on a résumé [3]. Other survey data shows that more than one in four Canadian workers and job hunters admit to this practice [3].

These actions are often a response to perceived market realities. About 41% of Canadians aged 35 to 54 said their age makes them less attractive candidates [3]. The practice has become more prevalent throughout 2026 as the hiring environment for experienced professionals becomes more competitive [1, 5].

Job seekers are increasingly viewing their professional history as a liability rather than an asset. While a long track record usually signals expertise, in the current climate, it can lead to an immediate rejection if a company seeks a lower salary bracket, or a different cultural fit [1, 2].

Some millennials are removing up to 10 years of experience from their résumés.

The rise of 'resume Botox' suggests a shift in the professional landscape where experience is no longer an absolute advantage. As the white-collar market tightens, the perceived risk of hiring 'overqualified' employees—who may command higher salaries or be less malleable—is driving candidates to strategically obscure their tenure to bypass automated filters and human bias.