About

I operate one of the largest life insurance call operations in the U.S., with tens of thousands of hours of recorded final-expense calls. We’re now building a system that can turn those raw call recordings into structured, monetizable intelligence — specifically identifying and scoring leads who may qualify for SSDI, Medicare, or related government or health benefits that frequently surface in these calls. Your job is to build the workflow and logic from audio → insight including converting all call recordings into text, storing structured transcripts in a database for further processing, using NLP, topic modeling, or keyword extraction to identify conversations mentioning SSDI, Medicare, or other qualification indicators (income, disability, health status, wholesale real estate, or whatever trends you notice.). Creating scoring rules or machine learning models that predict eligibility or cross-sell potential. Building a dashboard or tagging system that our team can use internally to sort and prioritize leads. Scalability: Designing a workflow that can handle large-scale transcription and analysis (thousands of hours/month). Optionally leveraging tools like Databricks, AWS, or GCP for scalability. Bottom line, you have to make us money. Turn our data into something monetizable. research, ask questions, figure out what has to happen to extract value from this data. To Apply: Please include: 1. A brief description of similar projects you’ve completed. If you haven't done this work before, tell me why you'd be a good fit. 2. Tools you’d propose for this workflow. 3. How will you attack this? 4. What questions do you have? 5. Please answer without using AI 6. (Optional) Links to any relevant GitHub or portfolio projects.