My natural personality has lead me to always be curious about learning more about a system and how all these gears moving affect it. This is done through both domain expertise, theory, and data. As a result, economics and financial markets have always been an interest of mine. To follow my passion, I have pursued an economics and statistics degree at UCLA to learn more and help with connecting the different datapoints. Following up with a masters in applied economics, I then applied these same concepts in my work as a data scientist to help find insights, help with storytelling, and add value. I am currently going back for degrees in analytics and computer science to help me in my mission. - Software: R, Python, Scala, PySpark, Stata, LATEX, SQL, Tableau, - Super energetic, passionate, spirited, and always eager to learn. Analytics Skills: - Data Cleaning: Python: pandas, numpy, R: dplyr, tidyr, - Data Visualization - (Python: matplotlib, seaborn, R: ggplot2, Tableau, Plotly) - Web Scraping - Python, BeautifulSoup, Selenium, Scrapy, R: rvest, Modeling: - Supervised learning methods (linear regression, logistic regression, decision trees, random forests, adaboost), - unsupervised learning methods (k-means, hierchical clustering) Soft Skills: - Communication, teamwork, adaptability, problem-solving, leadership