- Utilized various cloud computing tools and APIs in Google Cloud, Microsoft Azure, AWS, and Naver Clova in order to store and organize data, as well as to perform OCR tasks on PDF documents, tables, and images of financial analyst reports. - Used Pandas and Numpy to clean and preprocess data, and applied various machine learning algorithms to calculate target prices and weighted averages from thousands of analysts across a 5-year timeframe. - Worked alongside backend and frontend developers to migrate the main database from PostgreSQL to MongoDB, restructuring and redesigning the database, designs and functionalities of the platform.

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- Worked seven days a week with cross-functional teams of data scientists, software engineers, product managers and marketing professionals. - Focused on scraping, cleaning and preprocessing data, conducting regression analysis, and generating sales and marketing data reports and visualizations for large wholesale and cosmetics companies in Southeast Asia. - Cleaned data using Pandas and Numpy, filtering outliers and handling duplicates and missing values, and preprocessed features with Scikit-learn. - Independently conducted demand estimation with regression modelling, predicting the demand for new products based on data such as customer income, location, and the implementation of new features and technologies.

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- Contributed to full-stack web development projects for a team of ten developers. - Developed websites using Node.js and MongoDB - Used Heap and Google Analytics to gain insights on customer engagement, retention, and adding new features.

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