🔥 What's hot in the job market
Companies, roles and metros where JobWhat users' applications and saves are growing fastest. Week of Sep 14–Sep 20 vs the week before.
Hot jobs & titles
title families, not individual postings| # | Title family | Posted mid | WoW |
|---|---|---|---|
| 1 | Software engineering Remote (US) · Chicago · Boston | $165K | ▲ 15% |
| 2 | Data Remote (US) · Minneapolis · New York | $175K | ▲ 24% |
| 3 | Operations Chicago · New York · SF Bay Area | $95K | ▲ 19% |
| 4 | Finance New York · Los Angeles · Minneapolis | $110K | ▲ 23% |
| 5 | ML / AI Remote (US) · Salt Lake City, UT · Portland, OR | $180K | ▲ 14% |
| 6 | Design Remote (US) · Miami · Atlanta | $165K | ▲ 17% |
| 7 | Product management Portland, OR · Chicago · Boston | $225K | ▲ 18% |
| 8 | Engineering management Salt Lake City, UT · Portland, OR · Remote (US) | $205K | ▲ 44% |
| 9 | Marketing Remote (US) · San Diego · Los Angeles | $130K | ▲ 14% |
| 10 | Support Remote (US) · Austin, TX · Washington DC | $95K | ▲ 19% |
Rising metros
growth in share of US activity| # | Metro | Share | Δ |
|---|---|---|---|
| 1 | Portland, OR Software engineering · Other | 4.9% | +1.0 pt |
| 2 | Boston Software engineering · Other | 4.7% | +1.0 pt |
| 3 | San Diego Software engineering · Marketing | 3.6% | +0.5 pt |
| 4 | Washington DC Software engineering · Other | 3.2% | +0.5 pt |
| 5 | Los Angeles Software engineering · Other | 4.8% | +0.4 pt |
| 6 | Las Vegas Software engineering · Other | 0.6% | +0.2 pt |
| 7 | New Orleans Software engineering · ML / AI | 0.4% | +0.2 pt |
| 8 | Toronto Software engineering · Other | 2% | +0.2 pt |
| 9 | SF Bay Area Software engineering · Operations | 4% | +0.2 pt |
| 10 | Salt Lake City, UT Software engineering · Engineering management | 2% | +0.2 pt |
How "hot" is calculated
We weight applications 5×, saves 3× and views 1×, count each person at most once per company per day, and decay older days (half-life 3 days). A company must have at least 8 distinct job seekers this week and 20 weighted events. Growth is smoothed so small companies can't jump to #1 on a handful of clicks, and suspicious bursts are dropped.
Full methodology →A = Σ 0.5^(age/3) · (5·apps + 3·saves + 1·views)
growth = (A_this + 40) / (A_prev + 40)
heat = ln(1 + A) · clamp(growth, 0.5, 4)^0.7
eligible if people ≥ 8 ∧ A ≥ 20 ∧ max_share(any /24 or install) ≤ 20%
Week of Sep 14–Sep 20 · published Sep 23 · data through Sep 23