Fintech

Pricing Tool

Project by Sirajuddin Mohammed

The business problem and approach

Developed a machine learning-driven pricing tool for a financial marketplace, enabling new freelancers to set optimal hourly rates based on predicted project win rates. The tool leverages freelancer profile and rate data, offering actionable recommendations to boost win chances, streamline onboarding, and increase earnings. Deployed as a Flask API on AWS Lambda for seamless user access.

Implementation highlights

Built ML models predicting win rates using freelancer profiles and hourly rates, Launched tool via AWS Lambda & Flask API for real-time recommendations, Enhanced onboarding with data-driven rate suggestions to maximize project wins

Delivery and outcomes

21% rise in new freelancer project win rates

Technologies used

Python
Machine Learning
Flask
AWS Lambda
API
SQL

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