MOHAMMED SAHAL

Data Analyst
Bengaluru, IN.

About

Highly analytical and detail-oriented Data Analyst with a proven ability to translate complex data into actionable insights and strategic recommendations. Adept at leveraging advanced machine learning, deep learning, and statistical modeling techniques to solve real-world problems, as demonstrated by impactful projects in healthcare and predictive analytics. Proficient in Python, SQL, Power BI, and Tableau, I am committed to driving data-driven decision-making and delivering measurable value in dynamic environments.

Work

Agarwal's Eye Hospital
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Research Intern

Bengaluru, Karnataka, India

Summary

As a Research Intern at Agarwal's Eye Hospital, Mohammed developed and rigorously evaluated a deep learning model for classifying clinical eye images to enhance diagnostic accuracy.

Highlights

Developed a deep learning model using Convolutional Neural Networks (CNNs) to accurately classify clinical eye images across four critical conditions, enhancing diagnostic capabilities.

Executed comprehensive image preprocessing, including resizing, normalization, and data augmentation, to significantly improve model robustness and generalization for clinical applications.

Rigorously evaluated model performance through key metrics like accuracy, precision, recall, F1-score, and confusion matrix, ensuring high reliability and validity of the diagnostic tool.

Education

St. Joseph's University
Bengaluru, Karnataka, India

Master of Science

Big Data Analytics

Jain University
Bengaluru, Karnataka, India

Bachelor of Science

Data Science and Analytics

Languages

English

Certificates

Introduction to MongoDB

Issued By

N/A

Data Visualization

Issued By

Tata Group

Skills

Programming Languages

Python, R Programming, SQL.

Data Tools & Platforms

MS Excel, Power BI, Tableau, MS Office Suite, MongoDB.

Machine Learning & Deep Learning

Machine Learning, Predictive Analytics, Deep Learning, CNNs, Gradient Boosting, SMOTE.

Data Processing & Analysis

Data Analysis, Data Visualization, Data Modelling, Image Preprocessing, Contour Detection, Thresholding.

Libraries & Frameworks

NumPy, Matplotlib, Pandas, SciPy, Scikit Learn, Seaborn, OpenCV.

Soft Skills

Strong Communication, Storytelling with Data, Problem-Solving, Attention to Detail.

Projects

Hypertension Risk Prediction in Children (Ages 6-18)

Summary

Developed a machine learning model to predict hypertension in children (ages 6-18) using clinical features such as BMI, age, and lifestyle factors.

Morse Code Detection

Summary

Implemented an OpenCV-based algorithm to detect and translate Morse code from images and readable text, utilizing Python libraries such as NumPy and OpenCV.