I believe the best way to learn is by building things, asking questions, and understanding why something works- not just how to use it. My current focus is on developing a strong analytical foundation through real-world data projects before moving deeper into machine learning.

Currently seeking: Data Analyst roles | Open to ML-adjacent opportunities

• End-to-end data analytics projects (EDA → SQL insights → dashboards)

• Transforming raw data into actionable business insights

• Building a portfolio that bridges analytics → machine learning

Languages & Databases:

Data & Analytics:

Tools & Platforms:

End-to-end Healthcare Operations Analytics project analyzing 500 patient cases using SQL, Python, and Power BI to uncover revenue drivers, patient complexity, and operational performance.

Python (Pandas) EDA + MySQL queries → Power BI dashboard revealing patterns behind employee attrition. Understanding HR analytics at scale.

SQL + Power BI project uncovering customer behavior, sales performance, and business trends. Deep-dive into window functions, CTEs, and data storytelling.

I document what I learn- not just code, but the ideas, observations, and thought processes behind analytical decisions.

Building projects, documenting the process, asking questions that matter.

⚡ Here's a Fun fact: All the electrons in motion powering the global internet weigh roughly 50 grams- almost exactly the weight of a single medium-sized strawberry.