B

International Student Part-Time Job Matcher

3.20

Derivation Chain

Step 1 International student Confucian/traditional culture education MOU
→
Step 2 International student daily life settlement needs in Korea
→
Step 3 Part-time work permit-based job matching

Problem

International students at Korean universities on D-2 visas must obtain part-time work permits before taking jobs, but many fail to understand the permit conditions (20 hours/week, industry restrictions) or are exposed to illegal employment. Existing job platforms (Albamon, Alba Cheonguk) lack filters for foreign worker permit eligibility, wasting 2-3 days per application when students apply and are subsequently deemed ineligible.

Solution

Takes the student's visa type, semester, and permit status as input to automatically determine which industries and hours they can legally work, then filters job postings to show only compliant listings. For employers, auto-provides guidance on required documentation for hiring international workers (work permit, social insurance applicability) and offers multilingual employment contract templates (English, Chinese, Vietnamese).

Target: International students at Korean universities on D-2/D-4 visas, aged 20-30 / Self-employed business owners (restaurants, convenience stores, logistics) seeking to hire international students
Revenue Model: Per Transaction at ~$3.70 per job posting (employer-paid), free for students, Premium Subscription (priority listing + employment contracts) at ~$21.60/month per business
Ecosystem Role: Infrastructure
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
3.0/5
U Urgency
4.0/5
M Market
3.0/5
R Realizability
3.0/5
V Validation
3.0/5
NUMR-V Scoring System
N Novelty1-5How uncommon the service is in market context.
U Urgency1-5How urgently users need this problem solved now.
M Market1-5Market size and growth potential from proxy indicators.
R Realizability1-5Buildability for a small team with realistic constraints.
V Validation1-5Validation signal quality from competition and demand data.
Each dimension is scored 1-5 and weighted into grade S/A/B/C/D.
SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (70%)

Tech Complexity
29.3/40
Data Availability
20.8/25
MVP Timeline
20.0/20
API Bonus
0.0/15
Feasibility Breakdown
Tech Complexity/ 40Difficulty of core implementation stack.
Data Availability/ 25Practical availability and cost of required data.
MVP Timeline/ 20Expected time to ship a usable MVP.
API Bonus/ 15Bonus for viable public API leverage.
Total 100 points; below 50% is filtered out.

Market Validation (53/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
14.0/20
Revenue Signals
9.0/15
Pick-Axe Fit
10.5/15
Solo Buildability
5.0/10
Validation Breakdown
Competition/ 20Signal quality from competitor landscape.
Market Demand/ 20Demand proxies from search and mention patterns.
Timing/ 20Fit with current shifts in tech, behavior, and regulation.
Revenue Signals/ 15Reference evidence for monetization viability.
Pick-Axe Fit/ 15How well the concept serves participants in a trend.
Solo Buildability/ 10Practicality for lean-team implementation.
Total 100 points; below 50 is filtered out.

Technical Requirements

Backend [medium] Frontend [medium] AI/ML [low]
Dashboard