About Me

A passionate Data Scientist with expertise in machine learning, data analysis, and predictive modeling. With a Bachelor's degree in Computer Science & Engineering and hands-on experience in Python and SQL, I excel in deriving actionable insights from complex datasets. I have a proven track record in leading data-driven projects and implementing innovative solutions that drive business growth and efficiency. Let's explore the transformative power of data together.

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Experience

Data Annotator

Quantigo AI, 2019 - Present

  • Led a team of data annotators responsible for labeling large datasets for machine learning projects.
  • Conducted regular audits and provided feedback to annotators to maintain high data quality standards.

Education

Bachelor's in Computer Science & Engineering

Daffodil International University, 2022 - 2026

CGPA: 3.99/4.00

Higher Secondary School Certificate

Mohammadpur Preparetory School & College, 2019 - 2021

GPA: 5.00/5.00

Secondary School Certificate

B.C.S.I.R High School, 2009 - 2019

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GPA: 4.61/5.00

Projects

Real-Time Airbnb Scraper & Dashboard

Developed a web scraping pipeline using Selenium to extract Airbnb listings, host information, and user reviews. Created a PowerBI dashboard for actionable insights, enabling listing optimization. Built a sentiment analysis model to predict satisfaction levels from reviews, aiding strategic decision-making.

Potato Disease Detection Model Using CNN

Developed a Convolutional Neural Network (CNN) model using TensorFlow to detect diseases in potato plants. Leveraged advanced deep learning techniques to enhance the accuracy of disease identification, providing a reliable tool for early diagnosis and effective crop management.

Heart Disease Prediction Model Using Ensemble Learning

Implemented an ensemble learning model using stacking, bagging, and boosting techniques to predict heart diseases. Utilized various machine learning algorithms to identify the most impactful features on heart disease, enhancing prediction accuracy and interpretability.

Customer Churn Prediction With Synthetic Data

Handled an imbalanced dataset using sampling techniques like SMOTE, oversampling, undersampling, and KNN. Developed a machine learning model to predict customer churn, leveraging synthetic data processing methods to improve model performance..

Abdomen Disease Detection Using Transfer Learning

Implemented advanced transfer learning models, including ResNet50 and VGG16, for detecting diseases in abdominal images. Leveraged pre-trained networks to enhance model accuracy and efficiency, adapting these architectures for the specific task of medical image analysis to achieve improved diagnostic performance.

Skills

Programming Languages

Python Libraries

Software Skills

Certifications

IBM AI Engineering

Coursera | IBM, October 2023

Data Science Career Track

Data Science 365, November 2023

Applied Data Science Lab

WorldQuant University, March 2024

Front-End Web Development with React

The Hong Kong University of Science and Technology, January 2023

Get In Touch

If you want to hire me or have any questions about my work, please contact me through my email or LinkedIn.