*** Research findings: Amazon UX Researcher job application experience ***
(I'm a researcher, so here's my research report...)
== IN-DEPTH FINDINGS ==
1. Lethargic recruiter response times + emotionally detached communication style/tone can convey a sense of disengagement to applicants.
Interactions fell far short of industry peers in 3 key success criteria:
a. Be responsive: e-mails to the recruiter typically required 3-5 days for a response. In today’s competitive and fast-moving UX labor market, Amazon came across as curiously and uniquely disinterested in its own applicants.
b. Guide applicants towards success: Google and Facebook recruiters proactively guide applicants to ensure they understood where people typically go wrong, and offer tips for avoiding those pitfalls. This puts all qualified applicants on a level playing field.
c. Show an engaged style/tone: recruiter did not convey any emotional enthusiasm for Amazon or for the applicant’s possible career at Amazon. Instead, recruiter e-mails often came across as impatient and disinterested.
2. “Case study” interview content and scope can actively lead more senior applicants to deprioritize Amazon as an employer.
At Amazon, the third UX Research interview is the “case study” interview. In this project, applicants receive an ambiguously constructed, vaguely articulated, and broadly scoped project assignment, with in-built contradictions.
For example, an applicant may be asked to provide a specific research plan for a poorly defined and broad research area, coupled with plans for a specific research study in that area, as well as the preparation work to moderating several tasks of that study.
As designed, these case studies harm the applicant experience in 3 key ways.
a. They reflect little direct connection to the research areas or methods prevalent among the team for which the applicant is applying — let alone the passions or interests of the applicant. In other words, to high-skill and in-demand applicants, the projects can diminish interest in Amazon and the team for which they are applying.
b. They involve a needlessly excessive scope. While it’s common for tech companies to request pre-work of applicants, such companies typically tightly constrain the scope of this work to a 2-8 hour assignment. To do so, companies carefully ask for the minimal amount of original work needed to fill vital gaps from the interview process.
In contrast, Amazon’s broad assignment projects involve an implicit 3-5 day scope. This excessive scope places Amazon’s expectations of applicants far out-of-line with industry norms.
Candidates may (correctly) wonder why Amazon can’t evaluate the participant’s capabilities through just one of these exercises, as essentially all industry peers already successfully do.
c. Just as Amazon is evaluating applicants, applicants are also evaluating Amazon. What unintended signaling does the case study project convey to applicants?
Because a core skill in being a UX Researcher is the ability to efficiently reach high-confidence conclusions with minimal invasiveness on participants, it’s probable that Amazon erodes its credibility among UX Research applicants with this process.
In particular, applicants may reasonably be left wondering:
- Would Amazon also unproductively impose needless and excessive expectations on my personal time should I accept an offer?
- Would Amazon discriminate against me as a working parent? (as the interview process already tacitly discriminates against applicants who lack weeks of spare personal time to manage Amazon’s laborious process.)
3. Current application process poses an undue burden on applicants — despite peer evidence that it may not lead to more accurate hiring.
Amazon’s current UX researcher interview process involves 4 interviews, involving approximately two weeks of applicant projects, as well as the substantial interview prep time inherent in preparing for a full day of tech interviews.
Amazon is far from the only tech company that sets high standards on applicants, and is also far from the only one to ask how to achieve those standards efficiently, at-scale, and without undue burden on its applicants.
For example, Google formerly and famously imposed countless process steps upon applicants to avoid the proverbial “one bad hire”, but backed away after rigorously evaluating the predictive validity of these methods. In doing so, Google discovered that these extra activities in fact added negative predictive validity — in other words, they did not help reduce bad hires. But they did lead Google to lose countless high-quality candidates who would have succeeded at the company, depriving them of the very people they sought.