Monthly Market Report
October 2026 Job Market
67
postings scored across 58 companies
Fit scores, skill demand, salary transparency, ghost job analysis.
Key Metrics
67
Jobs Analyzed
▼ 899 vs September
58
Companies Hiring
unique employers
49
Avg Fit Score
▼ 1pts vs September
9%
Salary Disclosed
▼ 7% vs September
0%
Remote Listings
of all postings
0%
Ghost Signal Rate
▼ 2% vs September
Executive Summary
The scoring engine processed 67 job postings in October 2026, running them against active candidate profiles to generate 67 fit scores. That's down from 966 the prior month. The average fit score was 49 — lower than you'd want, and a sign that this month's postings had specific requirements that most profiles didn't fully meet. The average moved down 1 points from last month's 50. 1 postings (1%) crossed the 75-point threshold — the range where a application is worth serious effort. 52 postings (78%) scored below 60, meaning the fit was too thin to compete without significant profile improvement.
On the demand side, Bachelor's Degree, Communication Skills, Data Analysis led across all scored postings. The gap picture this month was relatively distributed, without a single skill dominating as a universal weakness. The L-level breakdown — which measures required skill depth from L1 (basic awareness) to L5 (architect-grade expertise) — reveals which skills are commoditized versus genuinely differentiating. Skills sitting at L3 or higher are where candidates get separated from the pack.
Only 9% of postings disclosed salary. The numbers below are directional; treat them as a floor, not a guarantee. Ghost job signals were relatively low at 0%, suggesting above-average listing quality this month. The salary data, skill rankings, and company breakdown below pull from the same scored dataset — not survey data, not self-reported figures.
Fit Score Distribution
How scored postings spread across the 0–100 range. Scores below 60 represent thin fit; 75+ is where applications compete well.
52
Below 60 (weak fit)
14
60–74 (partial fit)
1
75+ (strong fit)
Fit scores weight profile match at 70% and resume match at 30%. A score of 75+ means the candidate's skills, experience level, seniority, and logistics overlap enough to compete. See how fit scores work for the full methodology.
Top In-Demand Skills — October 2026
Ranked by how often each skill appeared in scored postings. L-level indicates the typical required depth: L1 is basic familiarity, L5 is architecture-level expertise. Skills above L3 signal roles where depth actually matters. Full skill profiles at /skills.
| # | Skill | Postings |
|---|---|---|
| 1 | Bachelor's Degree | 19 |
| 2 | Communication Skills | 6 |
| 3 | Data Analysis | 6 |
| 4 | Project Management | 5 |
| 5 | SQL | 4 |
| 6 | Python | 3 |
| 7 | Cross-functional Collaboration | 3 |
Depth levels (L1–L5) derived from how surrounding job description context describes required experience. See the L-level system explained. Browse all tracked skills at /skills.
Salary Insights
Based on 6 postings that disclosed compensation out of 67 total (9% transparency rate). Midpoint is used where both min and max are listed.
$181K
Median Salary
$185K
Average Salary
$150K
Floor
$220K
Ceiling
Remote vs. On-Site Compensation
$185K
Average — On-site listings
Top Hiring Companies — October 2026
Companies with the most active postings this month. Avg score reflects how well those postings matched the candidate profiles that viewed them. High ghost rates suggest the company posts frequently but may not actively fill those roles. Company profiles at /companies.
| # | Company | Listings |
|---|---|---|
| 1 | TikTok | 5 |
| 2 | 2 | |
| 3 | Salesforce | 2 |
| 4 | Deloitte | 2 |
Ghost Job Analysis
Ghost jobs are postings that show low hiring intent — old posting dates, no salary disclosure, and generic descriptions that suggest the role isn't actively filling. ShouldApply scores each listing across multiple quality signals. Learn how ghost job detection works.
0%
of postings with ghost signals
▼ 2% from September
0
postings with at least one ghost signal
67
postings with clean quality signals
Ghost signals are based on: posting age (45+ days), absence of salary data, and vague job description content. A listing can have one or more signals. The dashboard flags these automatically so you can deprioritize them. Full ghost job methodology.
Market Observations — October 2026
Patterns worth noting from this month's dataset. Not statistical projections — just what the numbers show.
Depth requirements are rising in specific areas
Bachelor's Degree, Communication Skills, Data Analysis averaged 3.8+ on the depth scale this month — meaning postings weren't looking for familiarity, they required working fluency. Skills at L4+ are where candidates get separated from the pile. Bachelor's Degree skill profile →
Salary transparency is still below average
9% of postings included compensation data this month. The median was $181K, which holds in line with market expectations for the skills in demand. State-level salary transparency laws (Colorado, New York, Washington) push overall rates up, but the remaining 91% of listings still leave candidates negotiating blind.
How This Report Is Built
Data transparency matters. Here's exactly what goes into these numbers.
Data Sources
Job postings are pulled from four sources: JSearch, Remotive, Adzuna, and Wellfound. Each source is refreshed every 2–6 hours. Cross-source duplicates are removed using a SHA-256 content hash plus Jaccard title similarity (threshold: 0.8) within the same company.
Quality filters remove thin descriptions (under 100 words), postings from blocked domains, and non-English listings. What's left goes into the scoring pipeline.
Scoring Methodology
Each posting is scored against a candidate's profile using a five-dimension model: Skills Match, Experience Level, Seniority Alignment, Industry Fit, and Logistics (salary, remote, location). The overall score is 70% profile fit + 30% resume match.
Skill depth (L1–L5) is extracted from surrounding context in the job description — not just keyword presence. SHA-256 input hashing prevents re-scoring identical profile+JD combinations, keeping the dataset efficient.
Ghost Job Signals
A posting is flagged as having ghost signals if it was posted more than 45 days ago and includes no salary data. This is one component of a broader additive ghost probability model (capped at 95%) that also weighs applicant count, vague description quality, and reposting patterns. See ghost job methodology for the full model.
Report Freshness
Monthly reports are computed from all jobs created during the calendar month. This page is cached with a 7-day ISR window — data updates weekly as new postings are scored. Salary figures use the midpoint of disclosed min/max ranges where both values are present. Minimums of 3 data points are required before salary stats are shown.
Frequently Asked Questions
How is the fit score calculated?
What is a ghost job?
How often is this report updated?
What does L1–L5 skill depth mean?
Where does the salary data come from?
What job sources does ShouldApply pull from?
How do I see my own fit scores against these postings?
How is this different from LinkedIn's job match percentage?
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