A highly motivated Data Analyst with a robust expertise in data cleaning, analysis, and visualization. Skilled in Python, SQL, and advanced data manipulation techniques, with a proven ability to transform complex data into actionable insights. Committed to leveraging analytical capabilities to support data-driven decision-making and deliver impactful business solutions.
Data analysis professional prepared to deliver impactful insights and drive business decisions. Adept in data visualization, statistical analysis, and database management, with strong focus on teamwork and adaptability. Known for reliability, analytical thinking, and results-driven approach. Skilled in Python, SQL, and Excel, ensuring robust data solutions and strategic recommendations.
This project seeks to establish a foundational understanding of risk analytics in banking and financial services,focusing on how data is leveraged to reduce the risk of financial losses when lending to customers.
Performed risk identification, analysis, and evaluation for a loan default prediction project, with the goal of
minimizing default risks.
Python Packages: Pandas, NumPy, Matplotlib, Seaborn
· Developed a Simple Linear Regression model to predict employee salaries based on years of experience.
Split dataset into training and test sets, and trained the model on the training data.
· Built data processing pipeline, model building pipeline, and prediction pipelines to understand experience
salary correlation. Deployed the model as a web-based tool using streamlit for real-time salary predictions.
· Python Packages: Pandas, NumPy, Matplotlib, Scikit-Learn, Pickle, streamlit
Data Bricks Certification
Data Bricks Certification