Location: Dubai, United Arab Emirates
Mobile: +971509524537 • WhatsApp: +601162078955
Master of Data Science degree with distinction (GPA: 3.98/4)
Kuala Lumpur, Malaysia
Feb 2018 - Oct 2019
B. Sc. degree in Computer Engineering; first rank (GPA: 93.9%)
Sep 2012 - Sep 2016
Data Science and Analytics Intern
Kuala Lumpur, Malaysia
April 2019 - July 2019
Data Analysis and Machine Learning: Pandas, NumPy, Scikit-learn, TensorFlow/Keras, XGBoost, LightGBM, etc. Also familiar with SAS and Hadoop ecosystem.
Data Visualization and Dashboards: Matplotlib, Seaborn, Google Data Studio, Follium for maps, etc.
Databases: SQL. Web Scraping: BeautifulSoup, Selenium, HTTrack.
Cloud Computing: Google Cloud Platform (BigQuery for big data, Compute Engine, and Storage), Amazon Web Services (EC2, S3, and Route 53).
Languages: English: fluent (TOEFL iBT: 102). Arabic: native.
YouTube Trending Videos Analysis: Analyzed data of 40,000+ YouTube trending videos to identify common patterns and get insights (Python, Pandas, Seaborn, etc.). Code and results: http://bit.ly/YT-analysis.
End-to-end data-science projects: Built a machine-learning system to predict house prices based on many characteristics like house size, construction year, etc. Project report and code: http://bit.ly/hp-pdf.
Kaggle Competitions: Participated in many machine-learning competitions on Kaggle. Some are:
Clustering and Comparing the Neighborhoods of New York City and Toronto: Clustering was based on the similarity between the venues in the neighborhoods. Foursquare API was utilized to retrieve venues data. Project page: http://bit.ly/clustnt.
Focus Phase: An open-source time-tracking command-line application with statistics and visualizations. It is built using Python and published on the Python Package Index. Github link: http://bit.ly/focus-phase.
S3upload: An open-source Python application that makes it faster to upload a large number of files to AWS S3. Github link: http://bit.ly/s3upload.
Analysis of Stock Prices in Malaysia: Stock-prices data for 1800+ companies was crawled from many sources for 3 months; then multiple analyses were applied including sentiment analysis, stock-prices correlation, investment recommendation, and clustering. Github (with PDF report): http://bit.ly/dm-assign; video: http://bit.ly/dm-vid.
IBM Data Science Professional Certificate (2019)