Nithesh Reddy Ramireddy

Detail-oriented data analyst with expertise in SQL, advanced Excel functions including Pivot Tables and VLOOKUP, and Python libraries such as Pandas and NumPy for comprehensive data analysis. Proficient in Microsoft Power BI for creating impactful data visualisations and skilled in statistical analysis and data cleaning techniques to ensure accuracy and reliability. Strong analytical thinking and problem-solving abilities drive actionable insights from complex datasets, supporting strategic decision-making. Dedicated to leveraging technical skills to optimise processes and contribute to organisational success.

• Data Science Fundamentals with Python and SQL(IBM)
• Cisco Certified Data Analytics Essentials (01/2024 - 03/2024)
• Excel Skills for Data Analytics and Visualization(Macquarie University)

Titanic Disaster Survival Analysis: Performed data preprocessing: Handled missing values, normalized data, and converted categorical variables to numeric formats., Engineered features: Created new variables (e.g., family size, title) to improve model accuracy., Applied machine learning models: Logistic Regression, Decision Trees, and Random Forest to predict survival. Achieved 98% model accuracy after hyperparameter tuning and cross-validation., Visualized insights using Python libraries (Matplotlib, Seaborn) to identify key survival factors such as gender, age, class. Conducted model evaluation using confusion matrix, precision, recall, and ROC curve.

Autonomous Credit Risk Detection Model: Built a machine learning model to predict credit risk using the German Credit Dataset. Applied preprocessing techniques like imputation and encoding, and implemented models including Random Forest, Decision Tree, and Naive Bayes. Achieved 73.5% accuracy with Random Forest and evaluated performance using ROC-AUC and classification metrics.