➤ Developing NLP, RAG, OCR, computer vision, and deep learning models, enabling accurate text extraction and analysis for financial and medical LLM projects.

➤ United States Army Reserve Staff Sergeant (E-6), Secret Clearance.➤ Deployed September 2023 to August 2024 to the Middle East. ➤ Graduated with Honor from Basic Leadership Course with the top academic GPA (3.93/4.00) and 2nd highest leadership attributes out of 63 non-commissioned officers. ➤ Contributions to mission success were recognized and awarded by the Command Sergeant Major at US Army Finance Management Command.➤ As a squad leader, successfully maintained everyone’s strong morale and ability to delegate.

➤ Developed and implemented an advanced estimator using real-time IoT and app data visualizations, enabling the company to focus on actual product capacity and significantly reduce marketing costs by optimizing resource allocation.➤ Led an NLP project using app (1.8 million MAU) reviews and search words to improve UI/UX, resulting in a 15% increase in active users and enhanced app reviews.➤ Set up a new product’s data science metrics and KPIs, and created a dashboard to monitor. ➤ Worked closely with fellow data scientists, data engineers, product managers, and key executives.

➤ Implemented data analysis, advanced machine learning models, natural language processing (NLP) from big data, so that businesses can provide customers with compliant customer services.➤

➤ Analyzed on system or data processes, data structures, analytical methods, and applying key techniques of data sciences (machine learning, data mining, analysis) to build high quality recommendation systems using Tensorflow and Keras.➤ Developed solution allowing highly effective presentation and engaging visualization for decision making.➤ Worked with other data scientists to develop a Python codebase for predictive and prescriptive modeling, along with the development of other data science capabilities.➤ Built data pipelines on large data sets with intensive joins and conditionals to prepare data for internal analysis and clients.

Final Project: Computer vision model to classify a person's image into the right gender and age - technology utilized: Python, Sklearn, VGG16, OpenCV, Seaborn, TensorFlow/KerasProject #1: Regression model utilized to prove how NFL teams' data and statistics control all-time winning rates.- technology utilized: Python, SQL, Spark, Pandas, Seaborn, Matplotlib, NumPy Project #2: NLP utilized to predict whether a fashion-related Tweet is from an individual blogger or online shopping mall. - technology utilized: Twitter API, Tweepy, Python, Pandas, NumPy, NLTK, Gensim, Matplotlib, SeabornCase Study #1: PandasUtilizing transportation data around the world, discovered how transit lines have evolved. Case Study #2: SparkWith a json file (746MB) of tweets during the 2017 French Presidential Election, cleaned and explored the dataset. Case Study #3: RegressionPredicted the sale price of a particular piece of heavy equipment at auction based on its usage, equipment type, and configuration.Case Study #4: NLPUtilizing a json file of UFO sighting reports was collected from The National UFO Reporting Center Online Database, discovered people from what states/country have the most UFO sightings, and visualized the data.Case Study #4: Movie Recommender Movie Recommendation system user based, content based, and combination based. Case Study #5: Credit Card Fraud DetectionReal world credit card fraud detection using NLP, RandomForest ML, Flask

➤ To validate data and interpretations, successfully used statistical techniques for hypothesis testing, targeting government's defense/aerospace contractors. ➤ Developed a trend forecasting framework to estimate the 10M+ products price in order to help the business take proactive merchandising decisions.➤ Optimized data collection procedures, generated and visualized reports on a monthly and quarterly basis. ➤ Expanded the company's international relationships with the leading aerospace/defense companies of South Korea. As an outcome, the company achieved the highest revenue record every quarter.

➤ Researched and introduced a new POS software to the restaurant. Not only taught myself how the software works, but created new functions and visualizations on top of the software, and created a solid and easy-to-follow written guideline for the present/future staff and the owner.➤ Responsible for different tasks such as restaurant marketing strategies, recruiting and training 15+ staff, overseeing food quality, developing menus as well as greeting and serving restaurant guests.

➤ Worked closely with a broadcasting team from the UK. Translated Korean to English and English to Korean. ➤ Communicated with 150+ candidates from 20+ countries, making sure that they had a great time in Korea, so they could bring out their best during the competition.