Overview
CareerTruss runs three separate numbers, and confusing them is the fastest way to misread the product. Career Score measures your profile. Match score measures fit between one profile and one listing. The comparison line is a confidence heuristic. None of them is a prediction of getting hired.
1. Career Score — profile strength
A 0–100 measure of how complete and employer-ready your profile is. It is deterministic and fully transparent: no hidden weights, no model, no ranking of you against other students.
| Component | Max | How it fills |
|---|---|---|
| Profile completeness | 20 | 8 basic fields: name, university, field of study, graduation year, phone, city, degree, branch |
| Skills | 20 | 4 points per skill — 5 skills maxes it out |
| Applications submitted | 20 | 4 points per application — 5 applications maxes it out |
| Resume | 10 | All or nothing |
| Portfolio links | 10 | ~3.33 per link across GitHub / Medium etc, LinkedIn and portfolio |
| Preferred roles | 10 | All or nothing — one stated role is enough |
| Saved opportunities | 10 | 2 points per saved role — 5 maxes it out |
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Severity bands
| Score | Band | What it means |
|---|---|---|
| 0–39 | Critical gaps | Ranking cannot personalise for you yet |
| 40–69 | Developing | Matching works, but evidence is thin |
| 70–89 | Strong | Competitive profile with clear intent |
| 90–100 | Complete | Everything an employer can evaluate is present |
The Next Action Engine reads this
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2. Applicant match score — fit for one role
Computed by scoreApplicant(profile, internship). Employers see it in the applicant pipeline; students see its components in the "Why this internship?" explainer.
| Signal | Points | Rule |
|---|---|---|
| Skill overlap | up to 55 | Proportional to matched ÷ required skills |
| No skills required by listing | 25 | Neutral credit when the employer declared none |
| Resume | 15 | Present or absent |
| Portfolio / GitHub, Medium / LinkedIn | up to 15 | 5 each, capped at 15 |
| Location | 10 | City matches a non-remote listing |
| Remote listing | 5 | Treated as neutral-positive |
| Education depth | 5 | University and degree both present |
| Score | Tier | Label |
|---|---|---|
| 85–100 | excellent | Excellent match |
| 65–84 | good | Good match |
| 40–64 | fair | Fair match |
| 0–39 | poor | Low match |
Warning
3. "You're ahead of ~X% of applicants"
This is a confidence heuristic, not a leaderboard. It is derived from the ratio of your matching skills to the listing's required skills — it does not query other applicants, and it does not know how many people applied.
- Derived from skill coverage on that specific listing.
- Hard-capped at 93% so it can never imply certainty.
- Recomputed on every view; it moves when your profile moves.
Rules that apply to all three
- Deterministic. Same inputs, same output. No randomness, no model drift.
- Capped. Automated match and competitiveness percentages never exceed 95%.
- Explainable. Every number can be decomposed into named contributions.
- Non-punitive. A low score restricts nothing. You can apply anywhere, always.
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