Nadi(m)
Welcome to my Portfolio Page!
My name is Nadimul Hasan, and I'm an avid geek and a seasoned weeb.
This site started as a side project to get my resume online
in hopes of casting a wider net and being able to connect with
other individuals.
When I'm not losing my mind trying to figure out how to get out of tutorial hell,
I'm most likely split between deciding whether to finish the next 400 episodes
of One Piece, or whether to finish Act 3 of Baldur's Gate.
Let's see how it goes!
Trying to make the Math, Math since '01.
Work Experience
Software Developer Co-op
May 2023 – Aug. 2023 · Toronto, ON
- ▸ Worked with the Android Mobile Team to improve the Crave, CTV, and Noovo streaming applications.
- ▸ Collaborated with team members to redesign the show page for the apps using Kotlin and Jetpack Compose.
- ▸ Used GraphQL to query backend sources to develop a new recommendations tab providing users with personalized content.
- ▸ Utilized Git and GitLab for version control and peer code review to ensure conformance to SOLID principles and the MVVM architectural pattern.
- ▸ Reviewed customer complaints to resolve issues and improve the overall quality of user experience.
Software Developer Co-op
Sep. 2022 – Dec. 2022 · Toronto, ON
- ▸ Worked with the Android Team to improve the Android Mobile Banking app for CIBC and Simplii Financial.
- ▸ Collaborated with team members in Agile Sprints to meet deadlines and resolve issues efficiently.
- ▸ Participated in peer code review to ensure app builds run smoothly across all client devices.
- ▸ Leveraged Git and GitHub for version control, ensuring thorough testing and issue resolution before any code merge.
- ▸ Applied prior Java knowledge to navigate the Kotlin codebase, developing features that contributed to a 4% improvement in performance and user experience.
- ▸ Utilized Kotlin with Dagger-Hilt for dependency injection and Retrofit for backend API communication.
Featured Projects
View all →Real Time Data Streaming Pipeline
A pipeline that constantly makes requests at intervals to the GitHub API and performs streaming operations on the data to display useful analytics on a dashboard.
Python 
Redis 
Docker 
Apache Spark Highlights
- ▸ Developed a streaming pipeline that displays real-time analytics of GitHub repositories on a dashboard.
- ▸ Used Docker containers to deploy the Spark cluster for distributed processing of API requests.
- ▸ Designed the dashboard using Flask to display the analytics results.
- ▸ Used PySpark to perform relevant stream operations such as filtering, Map-Reduce, and aggregation.
- ▸ Used Redis as a local cache for data, chosen because the project was scoped as a local setup due to API rate limits.
Imbalanced Learning with SciKit
A Python script that measures the performance of various classification models against an imbalanced dataset — one where the class distribution is heavily skewed, giving models misleadingly high accuracy.
Python Pandas Scikit-Learn Highlights
- ▸ Benchmarked multiple classifiers against each other: Decision Tree, KNN (k=1 and k=3), Gaussian Naive Bayes, Logistic Regression, MLP Neural Network, and Random Forest.
- ▸ Used Pandas DataFrames to preprocess and clean the dataset before training.
- ▸ Applied the best-performing model to an imbalanced credit card fraud dataset.
- ▸ Addressed the class imbalance problem to surface the minority class — usually the one of actual interest.