I'm a passionate Data Analyst with a strong background in extracting insights from complex data sets. I specialize in using Python, R, SQL, and various business intelligence tools like Power BI and Excel to drive data-driven decision-making. I love automating processes with Power Apps and Power Automate, ensuring efficiency and accuracy in data workflows.
- 🔭 I’m currently working on projects related to Machine Learning, Generative AI, Survival Analysis, Statistical Analysis, Dashboards, Automation, and Business Intelligence (BI).
- 🌱 I’m currently learning advanced techniques in "Machine Learning with Python and R", "Time Series Forecasting", "Power APP and Automation".
- 👯 I’m looking to collaborate on projects involving machine learning, generative AI, survival analysis, statistical analysis, dashboard creation, and automation. I'm particularly interested in contributing to open-source projects that focus on data science, AI-driven analytics, and business intelligence tools.
- 💬 Ask me about data analysis, automation, and visualization.
- 📫 How to reach me: [email protected]
- 😄 Pronouns: he/him
- ⚡ Fun fact: I love turning raw data into compelling stories as well as coffee enthusiast who codes better with a good brew.
Here are some of the tools and technologies I work with:
- Python: Pandas, NumPy, Matplotlib, Seaborn
- R: dplyr, ggplot2, Shiny
- SQL: MySQL, PostgreSQL, Microsoft SQL Server
- Power BI: Dashboard creation, DAX, Power Query
- Excel: Advanced formulas, Pivot Tables
- Tableau: Data visualization, storytelling
- R Studio: Data analysis and visualization
- Power Apps: Custom app development
- Power Automate: Workflow automation
Here are some projects that showcase my work:
Regression and Hedonic Price Modeling: Using R to conduct sophisticated statistical analyses that control for various property characteristics, ensuring that the observed effects on property prices are attributed accurately to micromobility proximity
An Unsupervised Machine Learning project using Python to Predict customers that would buy again based on purchasing behavior.