Year:
Mar 2024 - Apr 2024 (6 week)
Tools:
Python, Figma, Framer, Adobe Illustrator, Flourish
This project explores the challenges young people face in today’s job market. The topic was chosen in response to the growing sense among youth that finding a job has become increasingly difficult. While unemployment rates appear stable post-pandemic, the reality for many youth — particularly those just entering the workforce — is very different. The goal here is to use a data storytelling approach to illustrate this gap between perception and experience, with an accessible, visually engaging format.
Final Design
I structured my project into four key sections to create a clear and engaging narrative, each supported by research and statistics:
hen vs. Now – A comparison of unemployment trends, highlighting key events and changes between 2019 and 2025.
What’s Really Happening? – A closer look at youth-specific employment data to uncover hidden patterns and challenges.
What’s Holding Youth Back? – An exploration of contributing factors such as the rise of part-time work, the influence of AI in hiring, and increasing entry-level job requirements.
Where Do We Go From Here? – A forward-looking section offering reflections and possible next steps for both youth and employers.
My Audience
Audience
Primary: Youth aged 15–34 seeking work
Secondary: Parents, teachers, and mentors supporting youth career paths
Data Literacy
Assumed mixed levels of comfort with stats
Used clear, non-technical language
Added annotations and short explanations to guide understanding
Visual Strategy
Illustrations and color-coded sections for clarity and engagement
Avoided complex or overwhelming charts
Used visual hierarchy to help people get the point quickly
Data Management & Statistical Methods
I used data from Statistics Canada, which included a wide range of details — such as different geographic regions, labour force characteristics, gender, and age groups. To prepare the data for analysis and storytelling, I applied several data management techniques throughout the project:
Removed unnecessary columns
Converted dates to year format
Grouped data by year instead of month to simplify patterns
Filtered for youth aged 15–34
Focused on Canada-wide data
Renamed columns for clarity
And more…
These steps allowed me to clean and streamline the data, making it more relevant, focused, and easier to use for both analysis and visual storytelling.
In my final work, I mainly used simple statistics to highlight trends and comparisons over time. Throughout the project, I explored other statistical methods, such as confidence intervals, but chose not to include them in the final project. Given my audience’s varying levels of data literacy (and the time constraints), I felt it was more important to keep the analysis clear and approachable. That said, this is an area I’d like to explore further in future iterations.
Visual Identity
I chose Adelle for this project because it’s easy to read and has a modern feel that fits well with the overall design. Since the visuals were already quite rich, using a consistent typeface helped keep everything clear and simple.
I chose a palette that feels clean and professional but still has some personality. The deep blue, muted green, and gray tones set a more serious and structured tone—reflecting the routine and challenges that come with job searching. To balance that out, I added magenta and gold for warmth, creativity, and a sense of hope. These brighter accents help break the monotony and make the design feel more human and emotionally engaging.
