About Me
From Mechanical Engineering to Data Science
Hello, I’m Gregory Van, based in Renton, Washington. My journey began with a Bachelor's degree in Mechanical Engineering from the University of Florida, where I gained hands-on experience through internships at General Electric, Disney, and Boeing. After graduation, I joined Boeing as a Liaison Engineer, focusing on manufacturing commercial airplanes. Later, I transitioned into research and development, creating innovative fastening and assembly technologies.
Throughout my engineering career, I frequently encountered large datasets and complex analytical challenges, sparking a deep interest in data science. Driven by this passion, I pursued further education in data analysis and machine learning through platforms like Udacity and Coursera. I eventually earned a professional degree in Artificial Intelligence from Bellevue College and completed the Google Data Analyst program.
Currently, I work at Alaska Airlines as a Team Lead Pricing Analyst in Revenue Management. Some of my key responsibilities include building workflows to optimize daily operations, testing and implementing new pricing strategies, developing reports for business intelligence, and mentoring other analysts on the team.
Though I've had to learn many new skills in my transition to data science, one transferable skill that has been vital to my success is my ability to optimize processes to increase productivity, reduce errors, and improve modularity for changing business needs.
Core Skills:
Programming: Proficient in SQL, Python, and R, with experience in building data pipelines, automating processes, and developing algorithms.
Data Visualization: Skilled in creating insightful dashboards and reports using Tableau, PowerPivot, and Excel to communicate findings effectively to stakeholders.
Statistical Analysis: A strong foundation in statistics, including probability, regression, variance analysis, and hypothesis testing, built on my engineering background and advanced through recent courses.
Machine Learning: Expertise in applying machine learning models such as logistic regression, KNN, SVM, neural networks, and K-Means clustering using Scikit-learn, with real-world applications in optimization and prediction tasks.
Business Intelligence: Certification in Business Intelligence, with knowledge in relational databases and data visualization, helping to drive data-informed strategies.
Computer Vision: Basic understanding of image processing and object recognition using OpenCV, alongside experience in deploying deep learning models for image classification with TensorFlow and Keras.
I’m always eager to apply my skills to solve complex problems, whether optimizing business processes or building machine learning solutions. Please explore my Projects page to see some of my work!