Technically proficient Data Science and Engineering professional with a background in Engineering and a strong command of Python, SQL, and R for developing scalable, data-driven solutions. Experienced in applying machine learning, statistical analysis, and automation to solve complex business problems.

Skilled in building and optimizing supervised and unsupervised ML models (linear/logistic regression, clustering, anomaly detection) using NumPy, scikit-learn, and TensorFlow. Proficient in designing and training neural networks, implementing decision trees and ensemble methods, and developing recommender systems using both collaborative filtering and content-based deep learning approaches.

Adept at conducting statistical tests (T-test, ANOVA, regression analysis), interpreting results through hypothesis testing, and improving model performance by identifying and prioritizing high-impact data slices. Demonstrated ability to automate data pipelines, perform relational database operations with DDL, and extract insights using Python and SQL.

Dedicated to advancing AI/ML innovations through clean code, reproducible workflows, and a strong foundation in data analysis and statistics.