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hej6853/README.md

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Hi, I'm EunJeong, a Business Intelligence Analyst👨‍💻

I’m a Technical Product Manager, passionate about leveraging data-driven insights to solve complex business challenges!

🚀 Passionate About Data & Product Management I thrive in roles where I can apply data analysis, visualization, and interpretation to drive strategic decisions. Whether it's leading the development of Data Science solutions that save millions or optimizing processes to enhance user experiences, I love turning data into actionable business solutions.

💡 Technical Expertise & Continuous Learning My technical toolkit includes Python, SQL, Tableau, and more. I've also expanded my expertise through the USC Data Analysis & Visualization Bootcamp, where I honed my data analysis, machine learning, LLM, NLP and visualization skills. I'm always eager to learn and apply the latest tools and techniques.

🌟 Collaborative & Impact-Driven Collaboration is at the heart of my approach. I enjoy working in dynamic, cross-functional teams to deliver products that make a significant impact. From reducing operational costs to enhancing customer satisfaction, I aim to create value at every step.

🌍 Beyond Work Outside of my professional life, I’m an avid traveler and hiker who loves learning new languages and cultures. I also enjoy finding the perfect soundtrack for a good book.

🤝 Let's Connect! If you're looking for someone with a strong product management, data science, and business analysis background, I’d love to connect with you and explore how we can collaborate to achieve great things.

📧 [email protected]

EunJeong's GitHub stats Top Langs

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  1. Starbucks_People_Analytics Starbucks_People_Analytics Public

    Starbucks project shows how I utilized the ETL process using python pandas and matplotlib.

    Jupyter Notebook 1

  2. SQL-game_store_database SQL-game_store_database Public

    This a project that explains how I used SQL and ERD for a database design

    3

  3. Rowdy_Rooster_Project-2 Rowdy_Rooster_Project-2 Public

    This is a data visualization project using Python Flask, MongoDB, JavaScript, HTML and CSS.

    HTML

  4. Predicting_Useful_Reviews_On_Yelp_Dataset Predicting_Useful_Reviews_On_Yelp_Dataset Public

    This is a project to predict useful reviews on Yelp using Natural Language Processing with Python and RapidMiner

    Python

  5. Rowdy_Rooster_Project1-YouTube-Video-Trending-Analysis Rowdy_Rooster_Project1-YouTube-Video-Trending-Analysis Public

    This project used pandas, numpy, matplotlib.pyplot, seaborn, nltk and WordCloud python libraries to analyze "What is the special feature of popular videos?"

    Jupyter Notebook 1 2

  6. Nutrition-Project Nutrition-Project Public

    The nutrition project used ARIMA and Auto Regression model with python to predict the client's diet pattern and found positive and negative correlations between intake variables which have less tha…

    Python 2