Data Analytics Graduate | PM & Marketing Experience
Analytics graduate student with product management and marketing experience in the tech industry. Passionate about transforming complex data into actionable business insights that drive product decisions and user engagement. Currently seeking Fall 2025 or Winter/Spring 2026 internship opportunities in data analytics, product analytics, and business intelligence.
Learn about my background, skills, and career aspirations
I'm a dedicated Analytics graduate student at Northeastern University with hands-on product management experience in the tech industry. My unique background combines data science technical skills with real-world business experience in user behavior analysis, A/B testing, and product optimization.
With a Marketing undergraduate degree and PM work experience, I bring a business-first mindset to data analysis. I excel at translating complex analytics into actionable insights that drive product decisions, improve user engagement, and deliver measurable business impact. I'm actively seeking Fall 2025 or Winter/Spring 2026 internship opportunities where I can bridge the gap between data science and business strategy.
Featured projects showcasing my analytical skills and business impact across different domains
An innovative cinematic data analysis project examining movie box office trends through three distinct business perspectives: moviegoers, theater managers, and film producers. Rather than traditional presentation, I created an actual film featuring these three characters, where each role analyzes and visualizes box office data from their unique business standpoint, demonstrating how the same dataset yields different insights for different stakeholders.
Advanced statistical modeling and simulation project using R to analyze optimal betting strategies across multi-game sports series. This project combines probability theory, expected value modeling, Monte Carlo simulation, and chi-square testing to determine when betting on the favorite is most profitable in best-of-3, best-of-5, and best-of-7 series formats.
A comparison of cross-validation techniques and classification models using synthetic data. Includes evaluation of Logistic Regression, Random Forest, and SVM with K-Fold and Repeated K-Fold methods. This project investigates how performance stability improves with more validation cycles, featuring systematic model comparison and accuracy trend visualization.
Statistical and machine learning analysis of coffee bean prices using R. Includes EDA, ANOVA, and Lasso regression to understand how origin, roast, and ratings influence pricing. This comprehensive study applies time series forecasting techniques including STL decomposition, exponential smoothing, weighted moving average, and regression models with MAPE evaluation.
Time series modeling and comparative forecasting of AAPL and HON stock prices using regression, smoothing, and moving averages in R. This project explores statistical modeling to forecast stock prices and guide investment decisions, featuring ARIMA model forecasting, simulated trading strategy comparison, and comprehensive performance analysis with data visualization.
A linear programming-based simulation project for optimizing product mix decisions in a retail store. This analysis balances profit contribution, cost, and shelf space to recommend the most profitable inventory allocation strategy. Features constraint optimization, sensitivity analysis, and data visualization for retail analytics and supply chain management.
Interactive dashboard analyzing UK bicycle accidents (1979–2018) using Google Looker Studio. This comprehensive transportation safety analytics project demonstrates my ability to work with large-scale datasets and create compelling visualizations that could inform policy decisions and safety improvements across the UK transportation system.
An NLP project using vectorization, lemmatization, and Naive Bayes to perform sentiment analysis on Snow White text. This project showcases advanced natural language processing techniques including text mining and machine learning approaches - critical skills for analyzing user feedback, reviews, and social media sentiment in product management contexts.
More Projects
Coming Soon...
Let's connect to discuss internship opportunities, collaboration, or how data analytics can drive your business growth