“researcher”

Appeared in 1.2% of designer job listings the week of 2026-10-26 (7 of 589 postings).

First tracked 2026-04-13 · 17 weeks of collected data · peak prevalence 14% · no data collected Jul 27 – Sep 27

“researcher” prevalence in designer JDs, by week

2026-04-13 → 2026-10-26

% of each week's designer postings that mention this term · 17 collected weeks · peak 14% · 12 earlier weeks from before collection began not shown · hatched rows: no data collected, not 0%

2026-04-13
9.4%70/743
2026-04-20
3.3%2/61
2026-05-04
0.8%1/129
2026-05-18
2.8%1/36
2026-05-25
2.5%3/120
2026-06-01
3.1%6/196
2026-06-08
1.8%3/166
2026-06-15
14%33/234
2026-06-29
0.6%2/318
2026-07-06
2.8%8/283
2026-07-13
3.4%12/348
2026-07-20
3.4%4/117
2026-07-27
no data collected · 9 weeks, Jul 27 – Sep 27
—
2026-09-28
1.9%6/310
2026-10-05
1.1%4/365
2026-10-12
1.8%10/547
2026-10-19
1.5%9/590
2026-10-26
1.2%7/589

Where the conversation happens

Roles mentioning "researcher" over timeMentions of "researcher" across roles over 21 collected weeks. Top contributing roles: UX Researcher (198), Senior Product Designer (40), Staff Product Designer (23), UX Designer (4), Content Designer (2). No data was collected Jul 27 – Sep 27; that stretch is a gap, not zero.
Roles mentioning “researcher” by week. Stack ordered inside-out; thicker bands = higher mention counts. Hatched: no data collected, so the river breaks instead of dropping to zero.
UX ResearcherSenior Product DesignerStaff Product DesignerUX DesignerContent DesignerProduct DesignerPrincipal Product DesignerProduct Design ManagerOther roles
View as table
RoleTotal mentions
UX Researcher198
Senior Product Designer40
Staff Product Designer23
UX Designer4
Content Designer2
Product Designer2
Principal Product Designer2
Product Design Manager1
Design Engineer1
Design Lead1

Roles where “researcher” appears most

Ranked by share of the role's active listings that include this term. Roles with fewer than 20 active listings are left out.

About this tracker

Every active designer listing in our corpus is tokenized: HTML stripped, stopwords (common English words + job-posting boilerplate) removed, pure numbers dropped. The remaining tokens are bucketed into Monday-anchored weeks based on when each listing was first seen. Counts are weekly totals across every listing for that week. A week only counts as collected if our LinkedIn scrape (about 80% of volume) ran that week; weeks when it didn't are shown hatched as gaps, never as zeros.