Machine Learning Data Scientist

Mustafa Galal

Phone:996******* Email: **************@*****.***

WORK EXPERIENCE:

• A1 Stationery Retail Store – Sales & Operations Associate (Nov 2020 – July 2024)

• Handled inventory control, Purchase, and visual merchandising to boost sales.

• Maintained accurate sales records and supported promotional campaigns.

• Coding Cloud (Data Scientist) Oct 2024–Ongoing

• Built and deployed machine learning models using Python, improving prediction accuracy in real-world projects.

• Cleaned and preprocessed large datasets using pandas and NumPy, enhancing data quality for analysis.

• Wrote SQL queries for data extraction and transformation, supporting efficient data workflows.

• Collaborated on team projects, delivering end-to-end data solutions and presenting actionable insights. Technical Skills

Programming: Python, NumPy, Pandas, Scikit-learn, Matplotlib, Seaborn, MySql

Machine Learning: Regression, Classification, Cross-Validation, Decision Trees, Random Forest, SVM, AdaBoost

Data Handling: Data Cleaning, Feature Engineering, One-Hot Encoding, Outlier Treatment, SMOTE

Data Visualization: Matplotlib, Seaborn, Heatmaps, Boxplots, Power BI, Tableau

Tools & Platforms: Jupyter Notebook, Google Colab, Excel, Vscode Projects

1. Power BI / Flipkart Ravenue Analysis - D:\All google downloads\Power Bi Dashboard.pbix Objective: Analyzed Revenue of Flipkart to see its Profits and sales using visualization tools. Techniques: Through innovative data visualizations tools like clustered bar chart, donut chart, slicers I showcased the revenue& sales based on models and brands.

2. Machine Learning / Insurance Cost Prediction- inc_cost (1).ipynb Objective: Built a regression model to estimate a person's insurance charges based on age, BMI, smoking habits, childrens and region.

Techniques: Linear Regression, Random Forest Regressor, One-Hot Encoding, Zscore, mean squared error evaluation. 3. Machine Learning / Transaction Fraud Detection- Fraud_detection.ipynb Objective: Developed a classification model to identify fraudulent transactions. Techniques: Exploratory Data Analysis (EDA), Z-score, SMOTE for class imbalance, Random Forest, Adaboost. Certifications: Data Science + Data Analytics : (Coding Cloud Institute ) Education

Bachelor’s Degree 2019 (B.Com)

Grade: Higher Second Class Graduation, Year: 2019, Sinhgad College of Commerce Savitri Bai Phule University HIGHER SECONDARY CERTIFICATE (HSC)

Grade: First Class, Completion Year: 2016, Sinhgad College of Commerce, Pune SECONDARY SCHOOL CERTIFICATE (SSC)

Grade: First Class, Completion Year: 2014, New Dawn English Medium High School

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