• 📊 In just 2+ years as a Data Analyst, I've shown great results, including boosting sales by 12% and generating an extra $20k annually through advanced data analysis techniques like K-means clustering and Market Basket Analysis.
• 🔭 I have a Bachelor’s degree in Mathematics from UBC and am on track to graduate with a Master's degree from UCLA.
• 👀 I’m interested in data analysis, machine learning, and prediction related to product analytics and user experiences. My work often focuses on A/B testing, predictive analytics, reporting & insights, and defining new metrics.
• 😄 I primarily use Python, R, SQL, Tableau.
• 🌱 Since I lost access to my old account, I'm adding more of the projects I've been working on to this profile :)

I am a data analyst interested in uncovering insights and solving complex problems. I enjoy transforming data into actionable insights using R, Python, and SQL. I'm passionate about organizing and cleaning up messy data to create visually appealing graphs and charts that tell a story. Plus, I love using advanced techniques to predict future trends and outcomes based on historical data.

👩🏻‍💻 Languages and Data Analytics Tools:

➤ Python:

• El Nino Data Analysis in Python (numpy, pandas, scipy, sklearn, matplotlib)
• Statistical analysis and visual explanation of large climate data

➤ SQL:

• Sales Analysis with SQL

➤ R:

• Covid Cases Prediction (tidyverse, leaps, ggplot2)
• Wine Classification (tidyverse, randomForest, nnet, neuralnet, FNN)
• Predicting Economic Mobility (glmnet)

➤ Microsoft Excel: Pivot Tables/Charts, Index/Match, X/VLOOKUP, IFS, SUMIFS

👩🏻‍💻 Data Visualization Tools:
➤ Tableau (both Desktop and Public): Sales Dashboard
➤ Power BI
➤ Matplotlib

👩🏻‍💻 SQL: PostgreSQL, MySQL, Spark