Career Match

A platform that helps students explore tech careers aligned with their skills and goals. It educates users with guidance and actionable steps to confidently pursue those paths.

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Inspiration

As a high school computer science student, I noticed a major problem: my peers were confused about what careers were actually available in tech -- and how to pursue them. From AI and cybersecurity to game development and web design, the pathways were overwhelming, fragmented, and filled with vague advice.

In a survey I ran with 70 students, 84% said they wished they had step-by-step, personalized guidance for exploring and preparing for tech careers. That insight sparked the idea for CareerMatch, a platform built to simplify career discovery and planning for students like me.

How I Built It

CareerMatch is a full-stack web application built with:

  • Backend: Python with Flask
  • Frontend: Jinja2 templating and Bootstrap for responsive design
  • AI Integration: Google Gemini API for the career chatbot
  • APIs: CareerOneStop API for real career data
  • Storage: Flask session-based progress tracking (no login required)

I used a modular architecture to ensure the app could be extended easily in the future. All data is hardcoded or fetched on demand, and no user accounts are required, so it is demo-ready and privacy-friendly.

Key Features

  • Interactive Career Quiz that matches users to CS-related jobs based on interests and skills
  • Career Explorer with curated job info: salary, job outlook, skills, training resources, and videos
  • AI Career Bot for personalized, actionable advice (powered by Gemini)
  • Progress Tracking through unlockable badges and a gamified experience
  • Volunteer Finder Form that simulates local engagement and unlocks a badge

Challenges I Faced

  • Balancing Simplicity and Depth: I wanted to make the app extremely simple for students to use, but still provide in-depth, high-quality information. Designing a UI that supported both was challenging.
  • AI Prompt Engineering: Getting the Gemini API to respond like a high school-friendly career counselor required a lot of prompt tuning and response structuring.
  • Session-Based Architecture: I had to simulate user progress tracking without a database, which involved some creative use of Flask sessions and validation.

What I Learned

  • How to integrate AI into a web app in a way that feels purposeful and user-focused, not gimmicky
  • The power of combining gamification with guidance. Students will be more engaged when since there is visible progress
  • Importance of user-centered design, especially for high school students who are new to tech and careers
  • How to plan for scale, even in an MVP: using modular code, reusable components, and flexible data formats

Why It Matters

CareerMatch is a real attempt to bridge the gap between interest and action in tech career development for young students. It turns vague curiosity into real momentum, with personalized, step-by-step guidance. All in one place.

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