SkillsMatch

Students have skills. Employers have jobs. But finding the right match is still surprisingly difficult. That's where SkillsMatch comes into play.

Comment

Inspiration

My interest in computer science started long before I ever thought about internships or building a startup.

In Grade 9, I remember being fascinated by the idea that I could actually make a computer do something I had imagined myself. One of my first projects was a simple calculator. It was not an advanced application, but seeing something I had coded take an input, process it, and produce an answer completely changed the way I looked at technology.

I went from simply using technology to wondering:

“What else can I build?”

That curiosity eventually grew into a much deeper interest in computer science. Since then, I have worked on projects involving software development, AI, robotics, and assistive technology, while continuously improving my programming and problem-solving skills.

This fall, I started my first year at Simon Fraser University as a Computing Science student. As I began looking for internships, I encountered a problem that felt very different from the excitement of building projects.

I had skills. I had projects. But getting an opportunity to prove them was still extremely difficult.

As a first-year student, many internships expect previous professional experience. Even when I found positions where I felt my technical skills were relevant, I often wondered whether my application would ever make it far enough for an employer to actually see what I could do.

That led me to think about the problem from the employer's perspective too.

If a company receives hundreds of applications, how do they identify the students who genuinely have the skills needed for the role?

And more importantly:

What if hiring started with what someone can actually do, rather than what their resume looks like?

That question became the foundation for SkillMatch.

What it does

SkillMatch is a skills-first hiring platform designed to connect students and employers based on their actual capabilities.

Students can create profiles containing their skills, projects, experience, and career goals. Employers can create roles based on the specific skills and requirements they are looking for.

Our platform then uses AI to understand information from both sides and identify potential matches.

Instead of simply telling a student that they are “qualified” or “not qualified,” SkillMatch can show how strong their fit is and explain why.

For example, a student might be a 93% match for a software engineering internship because they have strong Python, DSA, and React skills, while identifying SQL as an area they could improve.

We also wanted to address another problem: self-reported skills aren't always enough.

That's why we incorporated AI-powered assessments and live proctoring into SkillMatch. Our goal is to move beyond simply asking students what they know and toward giving them a way to actually demonstrate those skills.

The platform is built around a simple workflow:

Build → Understand → Match → Verify → Connect

How we built it

We built SkillMatch as a two-sided platform with separate experiences for students and employers.

The student side focuses on creating a skills-first profile, discovering relevant opportunities, understanding their fit for different roles, and identifying skills they could improve.

The employer side focuses on creating roles, discovering suitable candidates, reviewing their skills and projects, and shortlisting promising applicants.

AI is used to help transform unstructured information such as resumes and job descriptions into structured skills and requirements. Those skills can then be compared to identify relevant opportunities and candidates.

We also designed the platform so that AI is not simply producing a score. The goal is to make the matching process explainable, so both students and employers can understand why a particular match was recommended.

For skill verification, we explored AI-powered assessments and live proctoring to help employers evaluate what candidates can actually do rather than relying entirely on self-reported information.

Challenges we ran into

One of our biggest challenges was deciding what to build within the limited time of a hackathon.

There are many directions we could take SkillMatch — advanced assessments, better matching algorithms, employer analytics, messaging, notifications, learning recommendations, and more.

We had to prioritize the core experience and make sure that the main idea could actually be demonstrated within the hackathon.

Another challenge was making AI useful without turning the product into a black box.

We didn't want AI to simply generate a mysterious “93% match” score. We wanted it to help explain the reasoning behind the recommendation and identify both strengths and gaps.

We also had to think about how skill verification and live proctoring could fit naturally into the hiring process without making the experience unnecessarily complicated for students or employers.

Finally, designing for two different users — students looking for opportunities and employers looking for talent — meant constantly thinking about whether every feature provided value to both sides of the marketplace.

Accomplishments that we're proud of

We're proud that we were able to take a problem we had personally experienced and turn it into a working product concept within a hackathon.

We built both sides of the platform rather than focusing only on the student experience, giving employers a way to create opportunities, discover candidates, review their skills, and shortlist them.

We're also particularly proud of the skills-first approach behind SkillMatch.

Instead of treating a resume as the complete representation of a candidate, we designed the platform around the idea that a student's projects, technical skills, demonstrated abilities, and potential should all contribute to how they are evaluated.

Another accomplishment we're proud of is integrating AI in a way that supports the actual problem rather than using AI simply because it is a hackathon.

Most importantly, we turned a personal frustration — being a first-year student trying to break into the internship market — into something we could actually build and demonstrate.

What we learned

One of the biggest things we learned was that using AI is not the same as solving a problem with AI.

We initially had many ideas for where AI could be added, but we had to constantly ask whether each feature actually improved the hiring experience.

A match percentage alone isn't enough.

Students need to understand why they are a match and what they are missing. Employers need to understand why a candidate was recommended rather than simply receiving a number.

We also learned how challenging it is to design for both sides of a marketplace. A product that is useful to students also needs to provide enough value to employers for the ecosystem to work.

Most importantly, this project taught us how powerful it can be to build around a problem you have personally experienced.

SkillMatch started from a frustration I encountered during my own first internship search as a first-year student, and that personal connection helped us stay focused on the problem we were actually trying to solve.

What's next for SkillMatch

SkillMatch is only the beginning.

We want to make skill verification more robust, improve the accuracy and explainability of matching, and eventually provide personalized recommendations based on the skills a student is missing for their target roles.

We also want students to have a more complete picture of their job-search journey — including which roles they are a strong fit for, which employers have viewed or shortlisted them, what skills they should improve, and how they can become stronger candidates.

Our long-term vision is bigger than helping someone find one internship.

We want SkillMatch to become a platform where students can continuously build, demonstrate, and discover opportunities based on their skills.

The same curiosity that started with building a simple calculator in Grade 9 is what eventually led me to build SkillMatch today.

And the idea behind it is simple:

Students shouldn't need the perfect resume to prove they can do the job.

We don't want to match resumes. We want to match skills.

Built With

Share this project:

Updates

Submission history