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+32% Successful Matches

Built a marketplace platform that improved job matching speed and applicant conversion.

Created an efficient on-demand recruitment marketplace for faster hiring outcomes.

Project: Job2Go

JobsMarketplaceMatching

Executive Summary

A quick leadership snapshot of platform scope, delivery approach, and measurable outcomes.

Industry

Marketplace / On-demand

Platform

Web

Tech Stack

React, Node.js, PostgreSQL

Result

+32% Successful Matches

Timeline

12 weeks

Service Category

Web Development

Type

Client Project

Live Product

Explore the live project surfaces across web and app platforms.

Problem

Client Background

Job2Go needed a scalable hiring marketplace connecting recruiters and candidates with lower operational friction.

Critical Risk Area

The legacy workflow delayed fill rates and weakened platform liquidity.

  • Slow candidate matching cycles
  • Manual job moderation workflows
  • Low applicant completion on mobile

Solution

Delivery Outcome

We implemented streamlined listing creation, match recommendation logic, and recruiter workflows in one product interface.

Why this approach

Marketplace growth depended on reducing time-to-match while improving user trust and completion.

Smart matching workflow

Recruiter dashboard

Applicant funnel optimization

Notifications and status tracking

Process

How we made key decisions, handled technical complexity, and applied engineering expertise to deliver measurable outcomes.

1

Product & Architecture Decisions

  • Separated candidate and recruiter workflows for independent scaling
  • Added event-based alerts for high-priority match actions
2

Technology Selection Reasoning

  • React stack for dynamic marketplace UI
  • Node.js services for matching and notifications
3

Complexity Managed

  • Reduced applicant drop-off on mobile steps
  • Improved moderation speed without compromising quality
4

System Design Approach

Delivered matching core first, then layered recruiter analytics and quality controls in sprinted releases.

Engineering Highlights

Key technical decisions that enabled production-grade reliability, maintainability, and system scale.

Backend Architecture Design

Separated candidate and recruiter workflows for independent scaling

API Integrations

Node.js services for matching and notifications

Performance Optimization

Optimized critical execution paths to improve response times and reduce operational overhead.

Scalability Considerations

Avg. Time to Match: 2.9 days

Data Processing Workflows

Built reliable data processing workflows with validation and observability across execution stages.

Tech Stack

A modern technology stack selected to maximize performance, scalability, and delivery speed.

Our stack is selected for reliability, maintainability, and production scale.

Core Stack

React
Node.js
PostgreSQL
Redis

Supporting Tools

We also work with a wide range of modern technologies based on project requirements.

Next.jsAWSNotificationsAnalytics

Infrastructure / Workflow

Git
GitHub
GitLab
CI/CD
Code Reviews
Agile
Testing & QA

Results

Measured outcomes across efficiency, scalability, and system performance improvements.

Efficiency

+32%

Successful Matches

Automation

-44%

Job Posting Turnaround

Scalability

+25%

Mobile Apply Completion

Avg. Time to Match

Before

4.5 days

After

2.9 days

Apply Completion

Before

48%

After

60%

Weekly Placements

Before

86

After

114

Business Impact Snapshot

  • Improved successful candidate matches by 32% and reduced job posting turnaround by 44%.
  • Job2Go improved marketplace efficiency and strengthened supply-demand liquidity through better matching operations.

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