Team100_CareerCompass

Inspiration

Fresh graduates face a fragmented job search landscape. While job listings are abundant, understanding job fit, tracking applications, and identifying which skills to develop are left to the individual. This often leads to decision fatigue and unfocused applications. We wanted to shift the job search from passive browsing to guided, skills-based career planning.

What it does

CareerCompass is a unified career discovery and planning platform for fresh graduates. It aggregates job listings into a single view and evaluates roles based on skills rather than job titles. By analysing users’ CVs and job descriptions, the platform provides transparent match scores, highlights missing skills, and prioritises relevant roles through a swipe-style interface.

Users can track applications across stages and receive a short, prioritised upskilling roadmap based on skills that appear most frequently across their target roles, ensuring learning efforts align with real market demand.

How we built it

We built a lightweight web prototype using a Python backend and a simple frontend interface. Instead of training custom machine learning models, we leveraged an AI API to extract skills from CVs and job descriptions, generate match explanations, and produce personalised upskilling roadmaps. Figma was used to design the user flow before implementing the functional prototype.

Challenges we ran into

Our main challenges were controlling scope within a limited timeframe and standardising unstructured job data. As a beginner team, coordinating backend logic, frontend integration, and data processing under time constraints was also a learning curve.

Accomplishments that we're proud of

We delivered a runnable end-to-end prototype that goes beyond job listings to provide actionable career guidance. The platform integrates job discovery, skill matching, application tracking, and upskilling recommendations into a single, coherent workflow.

What we learned

We learned the importance of focusing on user decision-making rather than feature quantity, as well as how to effectively use AI APIs to transform unstructured data into meaningful insights within a short development cycle.

What's next for Team100_CareerCompass

Next, we plan to improve skill matching accuracy, expand job data coverage, and integrate learning resources to directly support recommended upskilling paths.

Built With

• css
• html
• javascript
• papaparse
• pdf.js
• react18