Mohammad Saad

Driven by a passion for data and technology at BigData BizViz Technologies, I enhanced system performance and user efficiency through algorithm optimization and innovative features. Skilled in Data Analysis and effective problem-solving, Committed to work streamlined data visualization and improved data quality, demonstrating a commitment to excellence and a proactive approach to challenges.

Power BI Certification Training Intellipaat Softwares

PROJECT: USFDA Oncology Drug Approval Analysis

• Implemented Latent Dirichlet Allocation (LDA) for topic modeling to analyze patterns in USFDA-approved oncology drug Subjective Columns.
• Conducted comprehensive sentiment analysis to evaluate public response and implications of drug approvals under the AAP program.
• Performed statistical analysis using Chi-Square tests to establish significant relationships between variables.
• Developed data visualizations to effectively communicate findings and insights.
• Utilized Python for data preprocessing, analysis, and modeling.
• Applied descriptive statistics to quantify approval trends and population impact.

PROJECT: Scrolling Addiction And Consumer Behavior Analysis Using Personality Archetypes

• Conducted Latent Dirichlet Allocation (LDA) for pattern identification in consumer behavior data.
• Implemented Principal Component Analysis (PCA) for dimensionality reduction and visualization.
• Performed Chi-Square tests to establish statistical significance between personality types and shopping patterns.
• Applied Cross-tabulation analysis with correspondence mapping to visualize relationships.
• Utilized Python libraries (NumPy, Pandas, Scikit-learn) for data preprocessing and analysis.
• Developed sentiment analysis using NLTK and VADER for consumer response evaluation.
• Successfully analyzed 12 distinct personality archetypes and their correlation with 4 major product categories.
• Created detailed frequency distribution analysis revealing key consumer segments and their shopping preferences.
• Identified significant patterns showing 23.91% dominance of specific personality type in purchasing behavior.
• Generated actionable insights for personalized marketing strategies and product recommendations.

PROJECT: Impact of Diabetes Mellitus on Acute Coronary Disease

• Conducted comprehensive statistical analysis using Kruskal-Wallis tests for continuous variables (age, creatinine, hemoglobin).
• Discovered significant correlation (p=0.0258) between diabetes status and ACS types using Chi-square analysis.
• Identified strong association between vessel disease patterns and diabetes status (Chi-Square: 155.23).
• Established statistically significant relationships in creatinine levels across diabetes groups (p=0.017).
• Generated comprehensive statistical reports with actionable healthcare insights.
• Created visualization dashboards for complex medical data interpretation.