Transitioning into the job market as a first-timer, especially without guidance, can be incredibly challenging. In Nigerian universities, while we are taught the skills needed to contribute to the workforce, we are rarely taught the skills necessary to secure the jobs where we can apply them. This creates a significant gap, leaving most graduates to navigate the job search process alone. Many turn to personal research, which can be overwhelming and confusing for someone without prior experience.
Although numerous guides and professional training programs exist for job seekers, they are often generalized and fail to cater to an individual’s unique situation. This leads to knowledge gaps that can hinder a job seeker's ability to succeed in the process. For instance, a candidate might excel at finding and applying for jobs but struggle with interview skills. These gaps significantly affect their chances of securing a job.
When first-time job seekers finally land their first interviews, they often find themselves lacking real-world interview experience. While they may know what to expect in theory, they are rarely prepared to put that theory into practice.
This is why we created Jobrail — to provide a personalized, practical solution that helps bridge these gaps and guides job seekers effectively through every stage of their journey.
Jobrail is designed to help users gain practical interview experience and address their knowledge gaps by breaking the job-seeking process into four stages:
- Core Stage: This stage helps users identify and understand their key skills and how these can be used in the workforce.
- Preparation Stage: In this stage, users focus on enhancing their skills, building their portfolios, and learning how to craft impressive resumes and cover letters.
- Application Stage: Users learn how to navigate the job application process, from finding suitable roles to tailoring their applications for each one.
- Job Stage: This final stage guides users through the interview process, helps them negotiate offers, and prepares them for their first day on the job.
At any point in their journey, users will find themselves in one of these stages, and each stage has tailored learning modules to address specific knowledge gaps. This flexibility allows users to select relevant modules at any time to effectively navigate their job search.
Additionally, Jobrail features a practice section that offers mock interviews with AI tailored to specific job roles. After completing a mock interview, users receive feedback and suggestions for improvement, which helps them become more confident and better prepared for real interviews.
Jobrail is targeted at job seekers who are new to the job market, particularly recent graduates or those who have little to no experience in navigating the job search process. The platform provides personalized learning modules, mock interviews, and real-time feedback to help users effectively transition from acquiring skills to successfully landing a job.
- As a job seeker, I want to learn how to navigate each stage of the job search process so that I can secure employment confidently and effectively.
- As a first-time interviewee, I want to practice interviews with an AI, receive real-time feedback, and improve my performance.
- As a learner, I want a personalized learning experience that addresses my unique gaps, ensuring I am well-prepared for all aspects of job seeking.
- Users begin by signing up and completing a quick onboarding survey to understand their current job search stage and needs.
- Based on the survey results, Jobrail recommends specific learning modules that suit the user's stage.
- Users can access learning modules, participate in mock interviews, and receive feedback.
- After practicing, users can review their interview performance, see areas of improvement, and revisit modules to improve further.
- Once confident, users can apply for jobs, using Jobrail as a guide throughout the entire journey.
To see the full User Flow Diagram, kindly visit: https://miro.com/app/board/uXjVKjUJ-bU=/
Jobrail is a web-based platform accessible from any browser. We used the following tools and technologies to build it:
- Figma, Canva, Illustrator: These tools were used to create user-friendly, visually appealing designs. Figma allowed us to build interactive prototypes for user testing, while Canva and Illustrator were used for graphic design and branding.
- React, HTML, CSS, JavaScript: The core technologies used to build the interactive user interface, ensuring a seamless and intuitive experience for users.
- React.Domify: Utilized to render HTML content dynamically within React, allowing for flexible and dynamic user interfaces.
- Axios: Used for making efficient API calls to the backend, simplifying data retrieval and submission.
- Redux Toolkit: Integrated to manage global state, making data handling more consistent across the application. This was my first experience with Redux, and I learned how to efficiently manage application states and improve the predictability of state changes.
- React Router DOM: Improved navigation throughout the app, and I got to explore its new loader functionality for streamlined data fetching.
- Custom Hooks & Context API: Custom hooks were used to modularize different logic, making the codebase cleaner and reusable, while the Context API helped manage global states effectively.
- Google Gemini: Integrated as the AI model for conducting mock interviews, providing real-time interview scenarios for users.
- Node.js & Express: The backbone of the backend, used for creating RESTful APIs and managing server-side logic.
- MongoDB: Our primary database for storing user profiles, job modules, and feedback from interviews.
- TypeScript: Employed for improved type safety, making the backend codebase more maintainable and robust.
- Redis: Utilized for caching API requests and improving response times, particularly useful for repetitive interview data.
- WebSockets: Implemented for real-time features, such as chat-based interview practice, allowing for a more interactive user experience.