jameslamb/skills

This project is a career guidance tool that answers a common question: if you're moving into tech or switching roles within tech, which skills should you learn next? Instead of relying on generic "top ten skills" listicles, it tries to give you recommendations grounded in real job market data. The idea is to gather thousands of real job listings from the web, then use data science techniques to find patterns in what employers actually ask for. When a user tells the app about their background and goals, it matches that against the collected job data to suggest specific skills worth prioritizing. The project also explored predicting salary outcomes for different skill combinations and mapping common career transitions. The intended users are people navigating career uncertainty, especially those transitioning from other industries into tech roles. For example, someone moving from marketing into data science could use this to figure out whether they should focus on Python, SQL, or something else entirely. A product manager considering a pivot could check what skills tend to appear in the job listings they're targeting. This was built as a capstone project for UC Berkeley's data science program, so it's an academic proof-of-concept rather than a polished product. The README notes the team successfully scraped sample job descriptions and salary data as validation, and they considered additional features like interview response analysis and person-organization fit scoring, though it's unclear which of those made it past the proposal stage. The referenced Google Slides deck may contain more detail on what was ultimately implemented.