Data Analyst

I am a Data Analyst with an MSc in Statistics and strong foundations in data science, machine learning, and statistical analysis. I use Python, SQL, and Power BI to turn complex datasets into practical, decision-ready business insights.

I am experienced in cleaning, preprocessing, validating, and analyzing large real-world datasets. My analytical work includes exploratory data analysis, hypothesis testing, feature engineering, statistical modeling, and communicating findings clearly to stakeholders.

I build business intelligence solutions using Power BI, DAX, KPI cards, slicers, and drill-through dashboards. I enjoy creating self-service reporting experiences that help teams monitor sales, profitability, customer churn, and other key performance indicators.

I also develop machine learning solutions for regression, classification, and clustering problems. In a loan default risk prediction project, I built an end-to-end pipeline that achieved 86.18% accuracy and evaluated models using cross-validation, precision, recall, and ROC-AUC.

I extend my analytics work into deployable products by building FastAPI REST APIs, Streamlit applications, and PostgreSQL-backed prediction logging workflows. I maintain reproducible analysis processes with Git and GitHub and am comfortable working across the full analytics lifecycle.

I am seeking opportunities where I can apply my statistical knowledge, analytics skills, and product-oriented mindset to solve meaningful business problems with data.