Mohamed Arafaath Sathik Basha

As a soon-to-be graduate with a Master’s in Data Science and Business Informatics from Università di Pisa, I am passionate about turning raw data into actionable insights. Currently, I am completing my master’s thesis at the InfAI Research Institute, focusing on explainability in offline reinforcement learning for ICU ventilator management.

With hands-on experience in SQL, Python, Power BI, Tableau, and Excel, my journey—from cleaning complex datasets, building various ML models, and designing robust SQL data warehouses to creating dynamic dashboards—reflects my deep commitment to data analysis and storytelling.

💡 Key Highlights:
- Designed a Gun Violence Analysis project that optimized data uploads by 98% using SQL Server
and SSIS, culminating in an interactive dashboard showcasing six-year trends.
- Mastered Excel for advanced optimization and decision-making during my Erasmus semester at
NTNU, Norway.
- Created comprehensive projects like Netflix, Spotify and Telecom Churn Analysis, and a Bank Loan
Analysis using SQL, Excel, Power BI, and Tableau, featuring dynamic DAX measures such as
Month-to-Date (MTD), Previous Month-to-Date (PMTD), and Year-to-Date (YTD).
- My ongoing master’s thesis on explainability in offline reinforcement learning for ICU ventilator
settings bridges my data analysis expertise with machine learning, emphasizing autonomous
pattern recognition. I thrive on collaboration, problem-solving, and crafting compelling narratives
from data that drive business decisions.

I thrive on collaboration, problem-solving, and crafting compelling narratives from data that drive business decisions. Eager to leverage my skills in SQL, Python, Power BI, Tableau, and Excel, I aim to deliver insights that make a real impact. Let’s connect if you’re looking for a driven, analytical professional ready to transform data into strategic advantage.