Cynthia Dorcas Kalapala

Motivated individual with experience in business analytics and data visualization. Known for strong problem-solving abilities and technical skills, ready to support data-driven projects that enhance organizational performance.

 Infosystems for Analytics - Supply chain Management Systems For Amul

• Conducted an in-depth analysis of Amul’s supply chain and cooperative model, focusing on integration of information systems for milk procurement, logistics, and warehousing.
• Researched and evaluated the role of Transport Management Systems (TMS), Warehouse Management Systems (WMS), Automated Milk Collection Systems (AMCS), and Automated Storage & Retrieval Systems (ASRS) in improving efficiency, transparency, and resilience.
• Assessed challenges such as the bullwhip effect, data privacy, and high implementation costs, and provided strategic recommendations for optimization and risk management.

Advanced Big Data Computing - Predicting Cardiovascular Disease Through Data Analytics 

• Built machine learning models in PySpark to predict cardiovascular disease risk using a Kaggle dataset of medical, lifestyle, and demographic variables.
• Conducted data preparation, feature engineering, and statistical analysis (Chi-square, T-tests, correlation, logistic regression).
• Implemented classification models (Logistic Regression, Decision Trees, Association Rules) with an ROC AUC of 0.77.
• Delivered actionable insights on lifestyle, physical health, and dietary risk factors, supporting early prevention strategies.

Marketing Research - Clark University Campus Store  (Real-Time Project) 

• Conducted a real-time analytics project using survey data collected from students and faculty to evaluate purchasing behavior and satisfaction at the Clark Campus Store.
• Utilized SPSS for statistical analysis and Python (Pandas, Matplotlib) for data processing and visualization.
• Identified key trends in product demand, pricing, and customer satisfaction, and proposed strategies to optimize inventory and sales.

Visual Analytics and Business Intelligence - Impact of Social Media and Technology Use on Mental Health

• Analyzed relationships between social media usage, technology habits, and mental health outcomes (stress, anxiety, sleep quality) using Python and Power BI.
• Conducted both primary data collection (self-administered surveys) and secondary data analysis (Kaggle datasets on technology use and mental health).
• Explored how time spent online, age, and gender influence mental well-being and identified vulnerable populations.
• Applied descriptive statistics, logistic regression, decision trees, and visualization techniques to detect trends and correlations.

Machine Learning : Credit Card Transaction Fraud Detection

• Developed a machine learning system to detect fraudulent credit card transactions using a dataset of 1 million transactions from Kaggle.
• Preprocessed and engineered features including age groups, category risk, transaction time, and state-level risk, while handling imbalanced data with under-sampling techniques.
• Implemented and compared multiple models: Logistic Regression, Lasso Regression, Random Forest, KNN, SVM, and XGBoost.
• XGBoost achieved the highest performance with 94.56% accuracy, 94.3% precision, and 94.79% recall, identifying key predictors such as transaction amount, category risk, and age group.
• Provided actionable insights for businesses on situational security measures, demographic-based monitoring, and policy optimization to reduce fraud losses.

• Digital Marketing Certification
• PCEP-Certified Entry-Level Python Programmer
• SEMrush Academy Certification
• Acing Your Strategy: A Human Approach to Successful Business Planning
• Accelerating Digital Transformation

• BCG Data Science Simulation, Performed churn analysis with Python (Pandas, NumPy), engineered random forest model (85% accuracy), and delivered executive summary.
• Tata Data Visualization Simulation, Built decision-support visuals for senior leadership using effective data presentation.
• New York Jobs CEO Council Simulation, Debugged and added features in a billing system to improve invoice communications.
• Quantium Analytics Simulation, Analyzed transaction data for commercial insights and strategic recommendations.
• British Airways Data Science Simulation, Built predictive models and analyzed customer reviews to explore buying behavior.