Polaris
Development Case Study 02 / December 2024
A peer-guidance platform that connects students to mentors, helping them find career resources, apply to jobs, and grow their career network.
Python
Flask
Streamlit
MySQL
Docker
Git
Personal Project
Developer
The Problem
Students navigating the co-op and early career search often struggle to find tailored guidance from people who have successfully been through the process. Current university resources can be generalized, leaving gaps in specific industry knowledge and personalized support. Employers also lack efficient ways to discover and connect with students who fit their hiring needs. Advisors face difficulty managing these relationships at scale while ensuring quality mentorship.
The Solution
Polaris is a multi-user platform where students (mentees), alumni or upperclassmen (mentors), advisors, and employers collaborate to enhance career readiness and opportunities.
Mentees get matched with mentors in their field, receive guidance, build public profiles, and apply directly to positions.Mentors track mentee progress, offer targeted feedback, and receive advisor guidance. Advisors manage matches, host networking events, and oversee platform engagement. Employers browse student profiles, receive applications, and connect via events.
Key Design Decisions
01. System Design
A containerized microservices architecture with separate services for API, frontend, and database, orchestrated using Docker Compose.
02. API Design
RESTful API built with Flask to handle CRUD operations for user profiles, applications, event management, and chat. Ensures modular endpoints for each persona’s needs.
03. Database Schema
MySQL database with tables for users, mentorship_matches, events, applications, and chat_logs. Foreign keys ensure relationships between personas and their interactions.
User Research
Iteration
Feedback & Takeaways
01.
Gained experience with full-stack development using Flask + Streamlit
02.
Learned Docker containerization and environment configuration.
03.
Overcame team-based development challenges when building software with varying software development skill levels.
04.
In the future, add authentication for data privacy and security
05.
Enhance mentor-mentee matching with machine learning for better recommendations.