Mai Anh

Built and evaluated a multiple linear regression model (OLS) in Python to predict Spotify song popularity using 11 audio features such as danceability, energy, loudness, acousticness, etc., across a dataset of 168,405 tracks. Cleaned and normalized large-scale music dataset to standardize audio features based on a 0-100 scale to enable cross-variable comparison and reduce skew in distributional analysis. Detected and flagged multicollinearity between energy and acousticness (r = -0.75) and energy and loudness (r = 0.78), adjusting model interpretation accordingly.

Statistical Modeling & Analysis Project - BANA 372

(2026-01 - 2026-03)

• Built and evaluated a multiple linear regression model (OLS) in Python to predict Spotify song popularity using 11 audio features such as danceability, energy, loudness, acousticness, etc., across a dataset of 168,405 tracks.
• Cleaned and normalized large-scale music dataset to standardize audio features based on a 0-100 scale to enable cross-variable comparison and reduce skew in distributional analysis.
• Detected and flagged multicollinearity between energy and acousticness (r = -0.75) and energy and loudness (r = 0.78), adjusting model interpretation accordingly.
• Produced correlation heatmaps, box-and-whisker plots, and regression coefficient bar charts to communicate findings to non-technical stakeholders.

Product Pricing & Market Analysis Project - BANA 372

(2026-01 - 2026-03)

• Cleaned and preprocessed a 500,000+ row Walmart grocery dataset using Python (Pandas, NumPy) to support strategic planning around product segmentation.
• Used Excel pivot tables to ensure data accuracy for pricing analysis.
• Built interactive dashboards in Tableau and Excel to visualize pricing patterns across departments, brands, and categories, enabling stakeholders to identify revenue opportunities.
• Conducted exploratory data analysis to identify price distributions, segment product categories, and recommend strategic pricing adjustments.

Business Analyst Intern - Sabico Food Corporation

(2025-07 - 2025-09)

• Built a monthly sales performance dashboard in Tableau tracking 38,500+ units and $336K in revenue across 31 Costco roadshow locations.
• Cleaned and queried sales data using SQL to analyze unit performance by location, identifying Garden Grove and Senter, San Jose as top-performing sites out of 35 roadshows.
• Developed a sales forecast model projecting 161,450 units and up to 1.85M in revenue for FY2025, factoring in roadshow cadence, Costco launch timeline and seasonality.
• Synthesized operational assumptions (inventory, promotions and demand) into a structured data input framework to align forecasts with quarterly business goals.

Bachelor of Science - Business Analytics - Oregon State University (2027-06)