Welcome to my data analytics and machine learning portfolio! Over the past several months, I've built 11+ end-to-end projects that demonstrate my skills across SQL, Python, cloud platforms, BI tools, NLP and statistical/machine learning analysis. These projects span from fundamental concepts to advanced use cases and are designed to solve real business problems.
1. Tech StartUp Marketing Analytics: Cancellations & Customer Segmentation
- Analyzed operational performance and customer behavior for a tech startup using SQL queries, Python scripts, and Tableau visualizations. Applied statistical analysis (chi-square analysis and K-means clustering) to examine booking cancellations, recommending alternative investigative routes. Developed segmented strategies tailored to different customer groups to enhance service optimization and revenue growth.
- Leveraged PivotTables, PivotCharts, and KPIs to produce a dashboard for a food company that tracked revenue trends, identified high-performing regions, and optimized inventory based on top-selling products.
- Built an end to end ETL pipeline using Azure, Snowflake, and Python to extract, clean, and analyze customer feedback. It integrates AI-powered sentiment analysis via Azure AI Language to categorize feedback as positive, neutral, or negative, helping businesses assess their customer representative performance. The cleaned and processed data is then stored in Azure Blob Storage and loaded into Snowflake, where a structured view summarizes sentiment trends. Azure SQL Server and Data Studio were also used as an alternative way to query and view. These insights enable companies to optimize customer service, refine training programs, and improve overall operational efficiency.
- Used advanced statistical analysis (regression and predictive modeling) for an e-commerce company to identify optimal price points as well as forecast revenue over the next 12 months, enabling data-driven decisions in inventory planning, marketing spend, and sales strategy.
- Analyzed customer service call data to identify the primary drivers of repeat calls within seven days, revealing a key factor impacting First-Call Resolution (FCR) and Customer Satisfaction (CSAT). Using SQL, Python, and Azure OpenAI (ChatGPT), 3 primary reasons were responsible for customers needing to call back. Recommendations were made to rectify these issues to FCR and CSAT.
- Excel project addressing inventory and staffing needs for peak seasons for a zoo.
- Multi-country sales analysis with Power BI dashboard for regional sales performance for a posible expansion.
- SQL project that analyzises customer purcahse behavior for a music streaming platform to target personalized offers
- Google Looker Studio project that highlights differences in global population trends.
- API and web scraping projects that showcase techincal skills in pulling APIs and getting information from the web.
If you're a hiring manager or fellow data enthusiast, feel free to explore or contact me for more details or a live walkthrough of any project.