Machine Learning Data Science

MOHAMMED BADAR UZ ZAMA

Chicago, IL-*****

+1-872-***-**** *********@*****.*** www.linkedin.com/in/badaruzzama

EDUCATION

Master of Science in Data Science November 2024

DePaul University, Chicago, United States

Coursework: Data Science Fundamentals, Neural Networks, Deep Learning, Advanced Machine Learning, Python, Data Analysis, RStudio, Database Systems, Data Visualization, Data Regularization, Programming Machine Learning.

Bachelor of Engineering in Computer Science May 2022

BITS Pilani, Dubai Campus, Dubai, United Arab Emirates

Coursework: Data Structures & Algorithms, Database Systems, Compiler Construction, Digital Design, Microprocessors & Interfacing, Logic in Computer Science, Discrete Structures, Neural Networks, Computational Theory

SKILLS

Data Engineering:

Data Visualization, Data Warehousing, Machine Learning, Deep Learning, Exploratory Data Analysis, Building Prediction Models, Testing & Training Models, Improving Model Accuracy & Precision, Database Handling, Model Evaluation

Programming Skills: Python, HTML, C, C, R, MySQL, SQLite, PySpark, CSS, SAS

Software Skills: PySpark, MySQL Workbench, Tableau, R Studio, SAS, Apache Hadoop, Apache Spark, Microsoft Office Suite

EXPERIENCE

Project Manager Intern, Merck Pharmaceuticals, Dubai, United Arab Emirates June 2021 - January 2022

Led cross-functional teams to manage and deliver 20 data-driven social media campaigns per month, utilizing analytics to optimize performance and increase efficiency

Analyzed large datasets on competitor activity and user engagement metrics, leveraging insights to boost campaign views to 10,000 and refine content strategies

Hosted virtual client events on ON24, managing data collection and real-time analytics to boost engagement

Developed and maintained data pipelines, integrating campaign metrics for real-time analytics and reporting, improving data accessibility and insights

Data Operations & Project Manager Intern, Astrid Oasis, Dubai, United Arab Emirates June 2020 - August 2020

Maintained a database for allotting and tracking inventory for construction projects, ensuring accurate data management and real-time resource availability, reducing allocation errors by 15% and improving project efficiency

Identified potential issues to implement data-driven solutions that improved project outcomes and cost efficiency by 19%

Utilized cost analysis and performance data to ensure resource allocation

Automated data management processes using SQL for inventory tracking, ensuring data accuracy and reliably improving resource allocation efficiency

ACADEMIC PROJECTS

Enhancing manufacturing efficiency through AI, Advanced Machine Learning Project

Enhanced manufacturing efficiency through AI-driven predictive maintenance by 70%

Applied data pre-processing techniques such as SMOTE to address class imbalance, enhancing model sensitivity for failure detection and achieving a balanced F1-score of 96%

Improved model accuracy by 12% through feature engineering, including interaction terms and cyclic transformations

Life Expectancy Analysis

Led a group project to build a predictive model through advanced feature engineering techniques, improving accuracy by 12%.

Implemented K-means clustering to segment countries into 2 clusters, based on healthcare metrics, socioeconomic status, and mortality rates, providing actionable insights for policy-making.

Used PCA, Regularized Regression, and Clustering.

Capstone Project

Predict Bike-Sharing demand based on Temporal and Environmental Factors.

Applied Random Forest and Gradient Boosting to predict bike rental demand, delivering actionable insights for optimizing operations.

Utilized Python, scikit-learn, and Google Colab for data analysis, model development, and performance evaluation, enhancing technical proficiency in machine learning and data science tools.

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