How It Works

The Ghost Job Analyzer uses pattern recognition and data analysis to help you identify potential "ghost jobs" — job postings that may not represent actual hiring opportunities.

What Are Ghost Jobs?

Ghost jobs are job postings that appear to be open but aren't actually available or actively being filled. Companies might post these for various reasons:

  • To collect resumes for future openings
  • To appear to be growing or active in the market
  • To fulfill internal policies requiring positions to be posted publicly
  • To gauge the job market for certain skills or salary expectations
  • When they already have an internal candidate but need to post externally

Ghost jobs waste job seekers' time and can be frustrating to encounter during a job search.

How Our Analyzer Works

Our Ghost Job Analyzer uses a sophisticated pattern recognition system to evaluate job descriptions. Here's how it works:

  1. Text Analysis: We scan the job description for specific patterns, phrases, and characteristics commonly found in ghost jobs.
  2. Red Flag Detection: Our system identifies potential warning signs such as unrealistic requirements, vague descriptions, and other indicators of ghost jobs.
  3. Positive Signal Recognition: We also look for positive signals that suggest a job is legitimate, such as specific details about the role, team, and hiring process.
  4. Contextual Factors: When provided, we consider additional information like how long the job has been posted, whether it's been reposted, and the number of applicants.
  5. Probability Calculation: Based on all these factors, we calculate a "Ghost Job Probability" score from 0-100%.

Key Indicators We Look For

Our analyzer evaluates dozens of factors to determine if a job posting might be a ghost job. Here are some of the key indicators:

Red Flags

  • Excessive experience requirements
  • Unrealistic skill combinations
  • Vague salary information
  • Overuse of buzzwords
  • Unreasonable education requirements
  • Combining multiple roles into one
  • Lack of specific details

Positive Signals

  • Specific salary ranges
  • Detailed hiring process
  • Clear team structure information
  • Specific day-to-day responsibilities
  • Named contact person
  • Specific start dates
  • Detailed benefits information

Additional Factors

Beyond the job description itself, our analyzer considers these additional factors when provided. These are common indicators shown on most job boards (like LinkedIn, Indeed, etc.), so make sure to check for these details when analyzing any job posting:

Days Posted

Jobs that have been posted for an extended period (especially over 30 days) without being filled are more likely to be ghost jobs. Recently posted jobs (under 7 days) are less likely to be ghost jobs.

Reposted Jobs

When a job is repeatedly reposted, it can indicate that the company isn't seriously considering applicants or has unrealistic expectations.

Applicant Count

A high number of applicants (100+) combined with a long posting period can suggest that the company isn't actively reviewing applications.

Interpreting Results

Our analyzer provides a Ghost Job Probability score on a scale of 0-100%. Here's how to interpret the results:

0-29%: Low Probability

This job posting shows positive signs of being legitimate. It's worth applying if it matches your skills and interests.

30-59%: Medium Probability

This job has some concerning elements but isn't necessarily a ghost posting. Proceed with caution and do additional research.

60-100%: High Probability

This job posting shows multiple signs of being a ghost job. Consider focusing your efforts on more promising opportunities.

Remember: Our analyzer provides estimates based on patterns and indicators, but cannot definitively determine if a job is real or not. Use it as one of many tools in your job search.

Privacy Note: The job descriptions you enter for analysis are processed in your browser and are not stored on our servers. We take your privacy seriously. Read our full Privacy Policy to learn more.

Jobzlo predicts possible ghost jobs, but can't confirm with certainty.