Project Showcase

Academic Projects

Global Suicide Rate Analysis (R)
Uncovering Socio-Economic and Demographic Determinants of Global Suicide Rates

Analyzed 27K+ records across 1985–2016 to identify socio-economic and demographic drivers of global suicide rates. Applied machine learning models (regression, trees, boosting, SVM) using R to reveal strong correlations with age, gender, GDP, and HDI. Key findings showed higher suicide rates among males and older adults, with HDI showing a surprising positive link. Insights support targeted mental health policy development.

Analysing Sales Trends (Tableau)
Analyzing the impact of COVID-19 on a Global Electronics Retailer's Sales

Built interactive dashboards using Maven Analytics data to uncover sales, customer, and product trends for a global electronics retailer. Visualized KPIs like sales by year, region, gender, and subcategory using dynamic filters and parameter controls. Revealed key insights, including COVID-19’s sales impact and seasonal dips during tax season. Demonstrated strong data storytelling and user-focused dashboard design.

Forecasting COVID-19 Trends: A Cross-Country Analysis (R)
Analyzed COVID-19 trends using decomposition, smoothing, and regression models.

Conducted time series analysis of COVID-19 trends in the U.S. and Australia using decomposition, smoothing, and regression models. Used R (fpp3, tsibble, fable) to forecast key metrics like cases and ICU admissions. Disproved seasonal assumptions and applied Holt’s method and harmonic regression for improved accuracy. Findings supported public health planning and cross-country comparison.

Operational Analytics for UK E-Commerce (Excel Solver)
Pricing, Logistics, & Forecasting Optimization

Led a comprehensive analysis for a UK-based wholesale e-commerce company using real Kaggle data. Explored breakeven discounts, transportation cost optimization, inventory planning, demand forecasting, and regression analysis. Key insights included a 33.65% discount threshold, $25K shipping cost savings with a German warehouse, and accurate sales forecasts via Mean and Moving Average models. Regression results (R² = 0.94) highlighted quantity and price as key sales drivers.

Portfolio Risk & Return Analysis Using Beta Coefficients

Assessed risk-return profiles of California REIT and Brown Group vs. Vanguard Index 500. Calculated key metrics (returns, std. dev., beta, correlations) and built portfolios to evaluate total and systematic risk. Findings showed California REIT had lower beta and better diversification potential, leading to a recommendation for risk-averse investors.

Littlefield Technologies Operations Simulation

Managed factory operations in a real-time simulation to maximize cash flow over a 268-day lifecycle. Optimized capacity, inventory, order scheduling, and contract pricing. Conducted demand and queue analysis, resolved bottlenecks via phased machine purchases, and applied dynamic priority rules. Ranked runner-up, demonstrating strong skills in supply chain strategy and data-driven decision-making.