Hiring·Project 03

Resume Screening & Ranking

Score 100 resumes against a job description in under a minute.

-80%

Screening time

~15 /hire

Hours saved

Same rubric, every candidate

Consistency

The problem

Hiring managers lose 15+ hours per open role reading resumes that don't match. Screening is inconsistent, biased by fatigue, and bottlenecked on one person's calendar.

How it works

1
Upload the job description once - it stays cached for the whole batch
2
Drop in resumes (PDF or DOCX) - ranked in a single pass
3
Claude extracts skills, scores fit against the JD, explains its reasoning
4
Top 10% flagged automatically; full rankings exportable as a branded PDF

Under the hood

~20 sec

Per analysis

Resumes per run

Sonnet 4.6

Model

PDF

Branded report

Sample output

Ranked results

ana-silva.pdf

Strong senior candidate with direct experience shipping the exact stack the role calls for.

Fit score

Strengths

9 yrs TypeScript, React, Node.js in production
Led rebuild of dashboard in Next.js 14 at current role
Shipped Stripe-based billing redesign for 1,800+ teams
Mentored 3 mid-level engineers, runs code review clinics

Gaps

No explicit B2B SaaS startup experience listed (current role is Series B, close enough)

rafael-costa.pdf

Solid full-stack generalist, some gaps on the B2B SaaS side but ready to grow into the role.

Fit score

Strengths

6 yrs full-stack, React + Node on e-commerce platforms
Led migration of 600 merchants from legacy stack
Cut payment failure rate from 3.1% to 0.4%

Gaps

E-commerce focus vs B2B SaaS - adjacent but different buyer dynamics
No Stripe Billing mentioned (only payment capture)

marcos-oliveira.pdf

Backend-first engineer with real scale experience but recent frontend work is thin.

Fit score

Strengths

7 yrs backend, strong Go and distributed systems
Owns payment ledger doing 2M events/day
Cut p99 latency 40% across 3 services

Gaps

Limited recent React / Next.js work - primarily backend
No mentoring responsibilities listed in current role

Live demo

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