🔍 GigLens

India's First Gig Worker Financial Health Audit Engine

A production-grade financial analytics project that quantifies the financial vulnerability of India's 23.5 million gig workers.

Live Demo →

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📸 Screenshots

Landing Page

Live Analytics Dashboard

Financial Health Calculator

Report Page

About Page

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🎯 The Problem

India's gig workers exist in a financial blind spot:

• 23.5 million gig workers with zero institutional financial tracking
• No platform fully meets Fairwork India's basic fair work standards (2024)
• The average gig worker earns below city minimum wage after expenses

GigLens was built to fill that gap.

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🚀 What It Does

Feature	Description
GigLens Score	Personalised financial health score (0–100) across 5 dimensions
Live Dashboard	Platform and city-level risk analysis with deviation charts
SQL Analysis	SQLite-powered queries across 500 worker dataset
Python Engine	Scoring engine calibrated to real published research data
Report Download	Downloadable financial health report with recommendations

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📊 Key Findings

Metric	Value
Average GigLens Score	49.1 / 100
Workers in Critical Risk	45 (9%)
Workers Vulnerable	250 (50%)
Workers Stable	205 (41%)
Most At-Risk Platform	Ola (46.5 avg)
Safest Platform	Amazon Flex (51.2 avg)

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🧮 Scoring Methodology

GigLens Score (0–100) = Income Stability (25%) — Earnings vs city minimum wage

Expense Burden (20%) — Monthly expenses as % of earnings Benefits Gap (20%) — Insurance + savings coverage Crisis Resilience (20%) — Months of expenses in savings Platform Risk (15%) — Fairwork India 2024 platform score

🏗️ Project Architecture

giglens/ ├── data/ │ ├── gig_workers.csv # 500-worker synthetic dataset │ ├── scored_workers.json # Scored output from Python engine │ └── giglens.db # SQLite database ├── scripts/ │ ├── generate_data.py # Dataset generation script │ ├── scoring_engine.py # 5-dimension scoring model │ ├── load_to_sqlite.py # SQLite loader │ └── analysis.py # Python analysis + charts ├── src/ │ └── App.js # React frontend (5 pages) └── screenshots/ # App screenshots

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🛠️ Tech Stack

Data & Analysis

• Python (pandas, matplotlib) — scoring engine and analysis
• SQLite — data warehouse with 2 tables, 500+ records
• SQL — window functions, GROUP BY, variance analysis

Frontend

• React 19 — 5-page SPA with persistent state
• Custom trail cursor and hover animations
• Divergent bar charts, trend lines, shadow deviation visualisation

Deployment

• Vercel — live React app
• GitHub — version control

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📂 Data Sources

• PLFS Annual Reports (MoSPI)
• NITI Aayog Gig Economy Policy Brief 2022
• Fairwork India Reports 2022–2024
• IFAT Worker Survey Data
• Karnataka Gig Workers Bill 2023

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🚀 Run Locally

git clone https://github.com/jessicamathew31-coder/giglens.git
cd giglens
python3 scripts/generate_data.py
python3 scripts/scoring_engine.py
python3 scripts/load_to_sqlite.py
npm install && npm start

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👩‍💻 Built By

Jessica Mathew
MBA Finance & Technology · MIT ADT University, Pune
CBAP · CAP · Microsoft Project Management

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Built to solve a real problem — not just for a portfolio.

🔍 Try GigLens Live →