Hi, I'm Erick
Results-oriented Data Scientist with 4 years of experience and a strong foundation in Actuarial Science (BSc), with hands-on roles as both a Data Analyst and Scientist. I leverage the power of Machine Learning, Artificial Intelligence, and Deep Learning to translate complex data landscapes into strategic, actionable insights. My expertise spans the full data lifecycle—from robust data wrangling using Python, SQL, and R, to advanced analytics, Natural Language Processing, Generative AI, intelligent AI agents, and compelling data visualizations. I have a proven track record of delivering impactful, data-driven solutions across finance, healthcare, retail, and technology by tackling intricate challenges and driving innovation. Skilled in cloud computing, business intelligence, data engineering, big data, and computer vision.
My Projects
Mall Customers Segmentation Project
I completed a Customer Segmentation project using K-Means Clustering to identify distinct customer groups based on behavior and demographics. Using a dataset from Kaggle containing 200 mall customers with features like age, gender, annual income, and spending score, I applied exploratory data analysis and visualizations to uncover patterns. Leveraging Python tools such as Pandas, Seaborn, Matplotlib, and Scikit-learn, I implemented the K-Means algorithm to group customers into meaningful clusters. This segmentation enables targeted marketing strategies by helping businesses better understand customer preferences and optimize engagement.
British Airline Customer Sentiment Analysis
In this project, I analyzed customer reviews of British Airways by scraping data from Skytrax.com and applying Natural Language Processing techniques to uncover valuable insights. Using tools like NLTK, machine learning, and deep learning, I cleaned and processed the review text to perform sentiment analysis, topic modeling, and generate word clouds. The goal was to understand customer feelings, needs, and feedback to help improve service quality. I visualized the key findings in a PowerPoint presentation, combining clear explanations with impactful charts to highlight trends and sentiments in the customer experience.
Weather Prediction Project
In this Weather Prediction project, I explored the impact of current weather conditions on forecasting the next day's weather using historical data. The analysis aimed to answer the question: "Does today's weather influence tomorrow's?" By leveraging Python, Pandas, Seaborn, and Matplotlib for data analysis and visualization, along with regression techniques for predictive modeling, I uncovered patterns and relationships in the data. This project demonstrates how weather trends can be used to support short-term forecasting, which is valuable for planning and decision-making in weather-dependent economic activities.
Additional Projects
Explore my curated collection of projects on GitHub, featuring work in data analytics, tabular data science, natural language processing (NLP), and deep learning.
Skills
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