•Developed a social media analytics model to track customer sentiment and engagement trends across large-scale datasets. •Applied machine learning and NLP techniques to extract insights from unstructured social media data. •Improved campaign targeting strategy by identifying key engagement drivers and audience behavior patterns. •Collaborated with cross-functional teams to translate analytical insights into business strategies. •Built scalable data workflows for continuous monitoring of social media performance.

Built and compared ARMA, Prophet, and LSTM models for sales forecasting •Evaluated model performance using RMSE, MAE, and MAPE •Improved forecast accuracy through parameter tuning and model selection •Designed forecasts to support planning, inventory management, and revenue estimation

•Developed a hybrid recommendation engine combining collaborative and content-based filtering •Evaluated performance using Precision@K, Recall@K, and Hit Rate •Improved recommendation relevance and user personalization •Designed to reflect real-world recommendation systems used in digital platforms

• Completed training in core data science and analytics methodologies, including data analysis, data-driven decision making and business problem-solving. • Developed practical understanding of data workflows such as data collection, cleaning, analysis and interpretation. • Gained exposure to applying analytics techniques to real-world business scenarios and identifying insights that support strategic decisions. • Strengthened foundation for working with data tools, analytical thinking and delivering actionable insights

•Successfully completed an intensive curriculum focusing on Data Science & Analytics, encompassing statistical methodologies, data visualization techniques, and advanced machine learning algorithms. •Acquired adeptness in utilizing essential tools like Python, PowerBI, SQL, and Excel for proficient data manipulation and analysis, crucial for contemporary data science practices. •Honed practical competencies through immersive project-based learning experiences, working with authentic datasets representative of real-world scenarios.