👩‍🦱 Pronouns: She/her

• ♾️ I love data science, business, and providing delightful client experiences
• 🤓 I am obsessed with growing and learning new things every day
• 🇨🇴 I value diversity in the workplace.
• ♾️ I am mission driven and like to collaborate with people who share the same purpose to solve customer's most difficult challenges through data driven projects
• 📚 Technical programming skills in Python; Pandas, Numpy, Seaborn, Matplotlib, scikit-learn, SQL Databases, PowerBI, Tableau, expossure to AWS Glue ETL, AWS Sagemaker, AWS S3, AWS Athena.
• 📫 How to find me:
  • ⭐ LinkedIn
  • 📰 Twitter

• Eurobank Saves 2M+ in Marketingn Budget with Machine Learning - The purpose of this analysis is to help The European Bank to reduce marketing budget allocated to telemarketing campaigns by at least 50% while maintaining client conversions.

Tech Stack: Python; Pandas, Numpy, Seaborn, Matplotlib, scikit-learn

• Supervised Machine Learning: Predicting Credit Risk with Scikit-learn - (WIP) - The purpose of this study is to recommend whether PureLending should use machine learning to predict credit risk. Several machine learning models are built employing different techniques, then they are compared and analyzed to provide the recommendation.

Tech Stack: Jupyter, Python: Scikit-learn, Naive Random Oversampling, SMOTE Oversampling, Cluster Centroids, SMOTEEN, Random Forest Classifier, Easy Ensemble Classifier - AdaBoost

• Movies ETL - A company in the live streaming business. Their data science team would like to develop an algorithm to predict which low budget movies being released will become popular. In order to do that it's necessary to go through the entire Data Pipeline (ETL)

Tech Stack: PostgreSQL, RStudio

• Predicting Car Performance: Statistical Analysis using R - The purpose of this analysis is to help Mechacar's Manufacturing team to understand what car features impact car performance the most. The manufacturing team will incorporate the insights into the manufacturing process aiming to produce the best performing cars in the market, rebrand the company image, and regain market share.

Tech Stack: R, RStudio

• Big Data with PySpark & SQL: Analyzing Bias in Amazon Paid Review Program - The purpose of this study is to help the executive team of DreamGames, an online videogame vendor, to decide if by joining the Amazon paid review program will generate a positive return on investment (ROI).

Tech Stack: Google Colab, Python: Pyspark, PostgreSQL, AWS Database Service, Jupyter

• Shein Boosts Revenue by $5M+ By Understanding Consumer Trends - The purpose of this analysis is to help Shein boost revenue by $5 M by launching new product and eliminating drivers for low Review Rating.