Automation
Opportunity Sourcing and Scoring Engine
Built an automated system that sources healthcare data analyst job opportunities, scores each one against real skills and project history using AI, and filters out duplicates and weak matches before they reach the team. Qualified opportunities land in a tracking pipeline with a written rationale attached, so every score comes with context. The team now gets a ranked morning digest instead of manually scrolling job boards.
The Problem
A healthcare data analytics bidding team was manually scanning job platforms daily with no system to judge which opportunities were worth pursuing. There was no scoring, no duplicate detection, and no shared view of what had already been reviewed. This cost hours on poor-fit jobs and left no record of past decisions.
How It Was Solved
An automated pipeline pulls job listings on a schedule and accepts manual leads, normalizing everything into one format and filtering out duplicates before they're processed twice. Each opportunity is scored by AI against the company's real healthcare data skills and project history, producing a fit score, a win-probability estimate, and a short rationale. Qualified matches are pushed into a tracking system automatically, while weaker ones are logged separately rather than cluttering the main view.
The Outcome
The team now gets a ranked morning digest of only the opportunities worth their time, each scored and explained. Manual job hunting has been replaced with a five-minute review. Every opportunity, qualified or not, stays logged for full visibility into the process.