Rajashekar Ponnam

Computer Science and Data Science graduate with hands-on experience in Data Analysis, Python Development, and AI/ML Application Development. Proficient in Python, SQL, Pandas, Scikit-learn, and data visualization. Developed systems for Predictive Maintenance, Intelligent Code Review, and AI-Powered Candidate Ranking, applying analytical problem-solving and clean, modular software design.

Data Science Trainee Internship at YUVA (2026-08 – 2026-09)

• Performed data acquisition, cleaning, preprocessing, and validation using Python, Pandas, and NumPy, handling missing values, inconsistencies, outliers, and erroneous entries.
• Conducted Exploratory Data Analysis (EDA) using Pandas, Matplotlib, and Seaborn to identify trends, correlations, patterns, and anomalies.
• Applied 2 machine learning paradigms—supervised and unsupervised learning—using Scikit-learn, including clustering, feature engineering, model training, validation, and performance evaluation.
• Developed and evaluated deep learning models using TensorFlow, analyzing model performance and challenges including overfitting and resource constraints.
• Completed 6 end-to-end Data Science tasks covering data acquisition, preprocessing, EDA, clustering, supervised learning, and deep learning.

B.Tech in Computer Science and Engineering (Data Science) – Marri Laxman Reddy Institute of Technology and Management (2022 – 2026)

Intermediate in MPC – Prathiba Junior College (2020 – 2022)

SSC – Sri Vivekanandha High School (2019 – 2020)