TAILORED EMPLOYMENT:
PROJECT TITLE: iRecruit
DESCRIPTION:
Meta University Eng Project Plan Template
[iRECRUIT] Intern: [Henry Alumona] Intern Manager: [Lee Fu] Intern Director: [Gaby Nahum] Peer(s): [Ruy Gonzalez Hermosillo] GitHub Repository Link: [https://github.com/Henrywis/Capstone-project] Overview Category: [Recruiting]
Story: [A recruiting website strictly for students who fulfill diversity requirements, where users, in this case, students (and recruiters) have profiles, and students (users) get connected to the latest internship opportunities, based on their categories of interest. Every candidate application is done in the Application room of that job and candidates can get more listings based on the most clicked title feature. Candidates "may" be able to track the progress of each application to see which is Accepted, Rejected or Pending.] Market: [ college students] Habit: [Internship Recruiting Seasons] Scope: [Internship listings]
PRODUCT SPEC User Stories
Required: [x] User can login [x] User can create a Profile [x] User can search for job/internship opportunities [x] User can filter opportunities based on categories [x] User can apply for jobs directly through the platform [x] User can see more information about the job by hovering over the title (OR any other complex User Experience) [x] Loading state for any fetch delays
Optional (Stretch): [x] User can see their profile
- User can track progress of application, including seeing if application was Shortlisted, Pending or Rejected (UI done, algorithm next)
- User can get notifications on listings or recruiter interest [x] User can edit their profile information [x] User can provide feedback on their account
Screen Archetypes:
- Home/Dashboard Screen: Feed Screen
- Applications list/Rooms Screen
- Current Application Screen
- Recommendation/Status bar
- Profile Screen
- Feedback Screen
- About Screen
- Contact Screen
Navigation:
- Login/Registration Screen: Allows users to log in or register for a new account.
- Home/Dashboard Screen/Feed Screen: Displays a feed of internship/job opportunities based on the user’s categories of interest.
- Applications List/Rooms Screen: Shows a list of all the applications the user has submitted.
- Current Application Screen: Provides information about a specific application (including its status - Shortlisted, Rejected, Pending)
- Recommendation/Status bar: Shows the application status and suggested jobs (based on user interactions)
- Profile Screen: Displays the user’s profile information (and allows them to edit it)
- Feedback Screen: Displays a mapped user interaction based on the user's liked, disliked and preferred posts (preferred posts are any on which 'Start Application' is clicked)
- About Screen: Displays general information about the site
- Contact Screen: Displays the contact information of the admin customer service (Optional)
DATA MODEL USER: • username • password • email • staus • race/Ethnicity • gender/Sexuality • name
APPLICATION: • id • userId (foreign key) • jobId (foreign key) • status (Shortlisted, Rejected, Pending)
JOB/INTERNSHIP: • id • title • description • categories (not provided) • recruiters (optional) • applicants (optional)
API Routes:
- POST /api/login Logs in user with credentials
- POST /api/register Registers a new user with credentials
- GET /api/opportunities Retrieves a list of internship/job opportunities based on user’s interest
- GET /api/applications Retrieves a list of user’s submitted applications
- GET /api/applications{id} Retrieves detailed information about a specific application (application page particular to one job/internship)
- POST /api/application Submits a new application for a job/internship
- PUT /api/profile Updates the user’s profile information
- GET/api/profile{id} Retrieves the profile information of self/another candidate
- GET /api/recommendations Retrieves list of jobs after ranking performed
Technical Challenges //For your project, you should demonstrate that you can apply what you’ve learned so far and expand on that knowledge to write code and implement features that go beyond the scope of the projects you worked on during CodePath.
Technical Challenge #1 RECOMMENDATION ENGINE For this project, I will be developing a recommendation engine that suggests internship/job opportunities based on the user's previous interactions, using weighting factors like category clicks, time spent and what user searches in the following order:
- DATA GATHERING/COLLECTION:- I will track the user interactions (category clicks, time spent on each listing and search queries by the user)
- I will store this interaction data and the user profiles, jobs/internships in my postgreSQL database
-
DATA PROCESSING:- I will convert the data (categorical data such as category clicks) into numerical data to be stored in my database, suitable for analysis. Using TF-IDF Vectorization to covert the processed text to numerical representations to feed into the ranking model.
-
DEFINE SIMILARITY MATRIX I will be using the Cosine Similarity metric to measure the similarity between a user and the job/internship listing For this, I will be having a user-item matrix to have vector representations of listing against user and the attributes of each user-listing matrix are number of interactions.
-
RECOMMENDATION GENERATION Recommend listings with the higher similarity with the user’s interactions based on the calculated similarity scores.
-
PERSONALIZATION AND EFFICIENCY:I could incorporate additional weighting factors such as time spent on each listing, or by recent interactions to better refine the recommendation. Experimenting with different weight constants for each factor (time, recency, queries, category clicks) to optimize and personalize recommendations by filtering out irrelevant listings.You can incorporate additional factors such as the time spent on each listing or the recency of interactions to further refine the recommendation process.
Technical Challenge #2
SCALABILITY : Ensuring the system can handle a growing number of users, applications and listings without performance degradation through CACHING Caching involves storing frequently accessed data in a cache, which is a fast-access, temporary storage system
HOW?
- I will Identify Frequently Accessed Data
- Choose a Caching solution
- Determine cache expiration strategy
- Implement caching mechanism
- Update Cache
- Monitor and Optimize cache performance
Timeline Project execution will start in Week 4 of MU. Based on the previously defined requirements, user stories and technical challenges, use the following table to scope out and plan a timeline for deliverables over Week 4 - 9. You can be as detailed as you need, ranging from simply mentioning the user stories, or dividing them into sub-tasks.
You are free to modify the table, add / remove rows or columns, whatever fits your style! The important thing here is that you focus and prioritize certain aspects of your project so you don’t get behind and are ready to deliver the MVP - remember your required features should be code complete before the end of Week 8, including both technical challenges!
We also encourage you to leverage project tracking tools such as GitHub Issues or Meta’s internal Tasks / GSD tooling to keep manage individual units of work.
MU Week
Project Week 1 (Internship week 4) 07/03 - 07/07 [x] Database with object models created [x] User can see listings on landing page [x] User can log in/sign up [x] Page updates on login depending on user
Project Week 2 (Internship week 5) 07/10 - 07/ 14 [x] User can filter opportunities based on categories [x] User can search for job/internship opportunities [x] User can apply for jobs directly through the platform
Project 3 (Internship week 6): 07/17 - 07/21 [x] User can get job ranking and suggestion based on category clicks [x] dropdown for categories (consider icons too) [x] UI for either dropdown/categories/recommendation/profile - Implemented Carousel & Application page UI [x] User can see & edit their profile (stretch)
Project Week 4 (Internship week 7): 07/24 - 07/28 [x] User can see & edit their profile (stretch cont.) [x] User can get job ranking and suggestion based on category clicks
Project Week 5 (Internship week 8): 07/31 - 08/04 [x] User can hover over a listing to see more information [x] Loading State [x] Fix Signup to be strictly for Underrepresented Students. [x] Implement caching
Project Week 6 (Internship week 9): 08/07 - 08/11 [x] Implement caching [] User can track progress of application, including seeing if application was Shortlisted, Pending or Rejected. (Optional) (Only UI done) [x] Design extra ui for about and contact pages. [x] Fix bugs []/ Do demo
Project Week 7 (Internship week 10): 08/14 - 08/18 [] Codebase week
- Home
- Chats page display
- Profile page
- Notifications page
- Feedback form page
- Suggested Listings: leads to chat page
- Technology page
- Finance page
- Research page
- Design page
Note: Each example loads on the Chats page.
- Track Applications/Candidates bar
- See "API routes"
- Applications + Status bar
- Profile page
- Loading State
- Application page/Summary UI
- Feedback
- Fix SignUp
- Cache
