I’m a data-driven problem solver with expertise in Python, R, SQL, Power BI, Tableau, and Excel. I specialize in data analysis, machine learning, and transforming raw data into actionable insights through compelling visualizations and predictive models.
Welcome to my data portfolio!
As a data-driven analyst, I thrive on extracting meaningful insights from data to drive strategic decision making. My expertise spans across Python, R, SQL, Power BI, Tableau, and Excel, enabling me to handle various stages of the data lifecycle. I specialize in data analysis, machine learning, and transforming raw data into actionable insights through compelling visualizations and predictive models. I'm passionate about leveraging data to solve real-world challenges and continuously explore new technologies to enhance my capabilities. Explore my projects below to see how I apply these skills.
My technical toolkit allows me to tackle diverse data challenges from collection and analysis to modeling and visualization.
Here's a selection of my recent data projects, showcasing my analytical capabilities and technical skills.
A full-cycle machine learning project built to predict hotel booking cancellations. This project showcases the complete ML pipeline, from data preprocessing to deployment, featuring a Flask web application for real-time predictions and containerized with Docker for seamless deployment.
Designed and built a SQL Server data warehouse utilizing Medallion Architecture to integrate CRM and ERP data for advanced business analysis. This project involved extensive ETL pipelines, Star Schema modeling, and in-depth T-SQL analytics (trend, segmentation, cumulative, part-to-whole), culminating in comprehensive customer and product insight reports. Tools used include SQL Server, T-SQL, SSMS, and Notion.
A collection of dynamic and insightful data visualizations created in Tableau, transforming complex datasets into clear, actionable dashboards.
Built and evaluated multiple NLP models including spam detection, fake news classification, and stock sentiment prediction using classical ML and deep learning. Fine-tuned DistilBERT to classify consumer complaints with high accuracy.
Used Python to collect static and real-time data from the Capital Bikeshare API and stored it in a MySQL database. Analyzed station usage, bike/e-bike availability, and capacity trends, with interactive dashboards built in Power BI for actionable insights.
I'm always eager to take on new data challenges and contribute to impactful projects. Whether you're looking for an analyst for your team or want to discuss a data-related idea, feel free to reach out!