PEARL ANDREWS

Business professional with comprehensive background in analyzing complex data to drive strategic initiatives. Known for enhancing operational efficiency and supporting decision-making processes through detailed analysis. Highly collaborative team member focused on achieving results and adapting to dynamic business needs. Proficient in data modeling and process improvement.

Walmart Sales Forecast Modelling (Python)

• Led development of a time series-driven sales forecasting model on Walmart's sales data to create predictive models to guide strategic decision-making. Conducted data cleaning, preprocessing, and EDA on 45 stores. Implemented linear regression and tree-based random forest models, selecting the best-performing based on metrics. Delivered actionable insights for strategic decisions in new store ventures.

Data Driven Stroke Prediction (Tableau)

• Led this project using Tableau to predict strokes, from data gathering to logistic regression analysis. Transformed complex data into actionable insights through intuitive data visualization, supporting healthcare professionals in making informed decisions.

Fraud Detection in Synthetic Financial Data (Python)

• · Developed a machine learning pipeline to detect fraudulent transactions using synthetic financial datasets. Conducted comprehensive data cleaning and preprocessing, including feature scaling, encoding, and handling imbalanced data. Built and evaluated multiple predictive models, such as logistic regression, decision trees, and random forests, selecting the best-performing model based on accuracy and precision metrics. Delivered insights to enhance fraud detection systems and improve financial transaction security.

Communication
Personal Initiative
Teamplay
Organization
Goal Oriented
Problem Solving
Networking

Running
Travel
Internet Browsing
Listening Music