Data Analyst, Analytics and Data Solutions Unit @ Ministry of Labour, Immigration, Talent, Skills and Development (Jan 2024 - Present)
HR Data Analyst CO-OP @ Tapsell (Feb 2020 - July 2021)
- Streamlined the recruitment process by constructing and administering a robust data pipeline with SQL, resulting in a 13% decrease in processing time.
- Scrubbing existing human resources data with SQL and Excel, improved data accuracy and accessibility by 7%.
- Developed a web-based system for employee onboarding using Python (Django), reducing onboarding time by 19%.
Bachelor's degree in Computer Engineering from Amirkabir University of Technology (GPA: 3.7/4)
During my academic journey, I gained valuable experience as a Research Assistant at the Pattern Recognition Lab, where I developed a Smart Crowd-Counting System using Machine Learning. Leveraging tools like Keras, TensorFlow, and a pre-trained VGG16 model, I achieved pinpoint accuracy in feature map extraction. Additionally, I designed a decision-making system for mapping crowd-counting methods and created an intuitive web interface using Django, HTML, CSS, and JavaScript.
I have demonstrated my proficiency in data analysis and machine learning techniques in my projects. For instance, I classified patients to predict their risk of diabetes using data mining methods and developed a search engine to retrieve news articles based on user queries. I have also worked on projects involving pattern recognition which utilizes methods such as K-Means, Vector Quantisation, Color Extraction, Image Segmentation, Image Compression, Text Clustering, Jaccard Distance, Supervised Learning, PCA, Dimension Reduction, Orientation Detection, Image Binarize, Classification, K-NN, Regression, Minimum Distance Classifier, Optical Character Recognition, Bayes and database design, showcasing my skills in Python, SQL, and data visualization using tools like Scikit-Learn, Matplotlib, Numpy, and Pandas.
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