HirePadi Match Score Explained: How We Rank Jobs Against Your CV
PadiWhen you upload your CV to HirePadi, every job in your feed gets a score from 0 to 100. This isn't a random number. Here's exactly how it's calculated, and what you can do to improve it.
Step 1: CV parsing
When you upload your CV (PDF or Word), HirePadi extracts:
- Skills (technical and soft skills mentioned anywhere in the document)
- Job titles (all roles you've held)
- Experience level (inferred from years in each role)
- Industry context (sector, function, sub-function)
- Education (degree type and field)
The parser uses Claude (Anthropic's AI) to read your CV the way a human recruiter would. Not just keyword extraction. If your CV says "built and maintained PostgreSQL databases," the system understands that as a SQL / database skill even without the exact word "PostgreSQL" appearing as a header.
Step 2: Job embedding
Each job listing is converted into a 1024-dimensional vector using Voyage AI's voyage-3-large model. Think of this as encoding the meaning of a job (its requirements, responsibilities, and context) into a form that can be mathematically compared to your CV.
Your CV gets the same treatment. We generate a vector that captures the totality of your background.
Step 3: Cosine similarity
We calculate the cosine similarity between your CV vector and each job's vector. This gives a base match score between 0 and 100.
A score of 75–100 means strong alignment. Your background closely matches what this role needs.
50–74 is a partial match. You have most of the core requirements but may be missing specific tools or experience.
25–49 is a stretch role. You could apply but should tailor your CV heavily and address gaps.
0–24 is not recommended. Significant skill gap.
Step 4: AI scoring (top candidates only)
For jobs scoring above a threshold, a second AI pass (Claude Haiku) does a finer analysis. It identifies specific reasons your background fits, skills or experience the role requires that your CV doesn't show, and whether you should apply, tailor, or skip.
This reasoning appears in your job feed when you expand a listing.
What affects your score
Things that help
Explicit skills sections. If your CV lists "Python, SQL, Power BI" in a dedicated skills section, the parser picks these up reliably. If they're only mentioned in job descriptions, they may score lower.
Quantified achievements. "Grew revenue 40% in FY2024" signals seniority and impact, which affects role level matching.
Job titles that match industry norms. "Head of Growth" scores differently from "Growth Manager" even with identical responsibilities. Use the title your industry recognizes.
Recency. Skills used in your most recent role carry more weight than skills from 10 years ago.
Things that hurt
Tables and text boxes in your CV. These break parsing. The extractor can't read text inside Word tables reliably. Use a single column format.
Vague language. "Proficient in Microsoft tools" doesn't match a job asking for "Advanced Excel." Be specific.
Very short CVs. A one page CV with minimal detail gives the parser little to work with, leading to lower confidence scores.
Mismatch between target role and CV history. If your CV is 10 years of banking but you're applying for product management roles, the score will naturally be lower. In that case, upload a tailored CV that bridges the gap.
How to improve your match score
Update your CV. Even small additions (adding a skills section, spelling out tool names) can lift your match score 10 to 20 points.
Set your target role in Settings → Preferences. This guides the matching algorithm toward the right job families.
Check the "Gaps" section on any job you're interested in. This tells you exactly what your CV is missing for that specific role.
Use HirePadi's CV Tailoring. The platform can rewrite your CV to emphasise relevant skills for a specific job (available from the job detail view).
Why transparency matters
Most job platforms are black boxes. You don't know why a job appeared in your feed or why you were rejected. HirePadi shows you the score, the reasoning, and the gaps so you can make informed decisions about which roles to pursue and how to position yourself.
The goal isn't to hide the algorithm. It's to make you a better, faster job searcher.