Moving students from overwhelming job search to intuitive career discovery

When looking for a job, students are generally navigating three distinct phases of discovery, browsing and shortlisting. For Gen Z students entering a hugely competitive market, the legacy model of endless scrolling through heavily padded, marketing led listings is simply overwhelming. They don’t need a pretty interface that only shows two jobs at a time; they need a high utility system built for volume.

To solve this, I shifted the product’s visual and structural language from an editorial, marketing first experience to a high density, system led model. By looking at how digital native students naturally explore and organise data, I designed a two stage triage system heavily inspired by the way people manage email. The goal was simple. Separate quick decisions from deep research, giving students a powerful workspace to filter, favourite, and manage their recruitment cycles at scale.

For the tracker interface, I experimented with several different layouts, from standard cards to a hybrid card and table setup, but ultimately chose a high density table view optimised for rapid decision making.

Under the hood, trackers are essentially just smart saved searches. Any time a student saves a search, it automatically creates a tracker, and we use their engagement data to suggest other trackers they might want to add to their list.

By stripping back the interface to showcase only the essential metadata, like organisation, role, location, and closing date, students can quickly scan their trackers and flag roles at scale. This was a deliberate choice of function over form. Rather than trapping newly tracked jobs in pretty cards where you can only see two at a time, the high density table lets students process as many roles as possible in one glance.

This view is all about quick decisions over deep research, letting students build up their shortlist of favourite jobs without getting overwhelmed.

The core idea behind the tracker was to let users set notifications for whenever new or upcoming roles hit the platform. We also flag when a favourite role is closing soon, which is crucial because our data shows that the vast majority of students submit their applications within the final few days before the deadline.

Taking another cue from email psychology, we introduced a distinction between a job being brand new and a job simply being unread, or not interacted with. This stops students missing new opportunities if they log back in on a different day and assume they have already reviewed everything. While we do have a dedicated recent activity feature, this unread state provides a much quicker, upfront indicator right where they need it.

Once a student flags a role, it moves into the jobs shortlist, where the detailed work happens. Here, the interface shifts from rapid triage to focused work, with the layout space needed for deep research and application tracking. Within this workspace, I implemented manual status progression logic for stages like applied, interviewing, and offer, which successfully centralised the student’s entire search history in one reliable place.

In this view, the student can dive deep into the details without losing their place. I structured the layout to pull in a comprehensive summary of the organisation’s profile alongside the full job description, allowing students to evaluate the opportunity and apply directly from this screen. By keeping everything in a single, focused workspace, we removed the need to constantly jump between tabs and browser windows during the application process.

Replacing the student’s manual spreadsheet with an intuitive workspace did more than upgrade the UI. It shifted their mental model. And the product goes beyond simple tracking. I designed it so students can browse opportunities, shortlist favourites, and discover roles they’d never have considered. Drawing on their profile and how they engage with the platform, the system quietly surfaces personalised matches in the background.

The build is preparing for launch, so live metrics are still pending. But the hypothesis is clear. A platform students reach for daily, rather than a marketing site they occasionally visit, should lift both their return rate and the volume of applications they make.