What is a job fit decision engine?
A job fit decision engine reads your background against a job description and gives you a verdict on whether to apply, with the reasons behind it. Where a résumé matcher counts shared keywords, a decision engine weighs what the job will screen you on.
Most job fit tools stop at a match score. A decision engine takes the next step and tells you what the score means for this one posting: go after it, think it over, or let it go.
It does not apply for you. The verdict is advice, and the decision stays with you.
How does a job fit decision engine work?
It works in four steps: input analysis, multi-signal scoring, risk and ghost job checks, and an actionable verdict. Each step answers a different question about the same posting.
- Input analysis. Your background goes in once, from the résumés and LinkedIn profile you already have. Each job description is then read for what it screens for, not only what it lists.
- Multi-signal scoring. The fit is scored on separate measures, such as background alignment, scope, seniority and the kind of work, rather than one keyword count.
- Risk and ghost job checks. The posting itself is examined for the marks of a ghost job, one written around someone already chosen. A posting that shows them cannot earn a Pursue.
- Actionable verdict. The scores become one call, Pursue, Conditional or Pass, with the reasons written out so you can disagree with them.
How is a decision engine different from a résumé matcher or ATS checker?
A résumé matcher assumes you have already decided to apply and helps you get past the filter. A decision engine works one step earlier, on whether the application is worth sending at all.
Both read the same job description. The matcher asks which words your résumé is missing. The decision engine asks which missing requirements will end the application and which are wish-list items nobody will test.
What does ArcLens score?
ArcLens scores ten measures, from background alignment and scope to risk and time to impact, and shows every one of them in a grid rather than hiding them behind one number. The verdict comes from the grid, so you can see why it landed where it did.
Each measure is scored for every Lens you keep, one for each direction you are considering. The same posting can be a strong step up and a poor lateral move, and the grid shows both at once.
Does a decision engine apply to jobs for me?
No. ArcLens gives you its call and the reasons behind it, and every application, edit and decision stays yours.
That is the difference from auto-apply tools, which send applications in volume on your behalf. A decision engine exists to help you send fewer, better-chosen ones.
How ArcLens scores your fit and reaches its verdict →