Gurugram, Haryana, India
The transition from academia to industry has been invigorating as I apply my Mechanical Engineering background from IIT Roorkee to drive data-led innovation at Bharat Petroleum. As a Data Analyst , I’ve leveraged analytical rigor and technical depth to enhance inventory management and customer satisfaction — achieving a 15% reduction in stockouts and a 30% improvement in reporting efficiency. My journey into advanced analytics deepened through developing CNN-based Next Best Action (NBA) models for rare disease brands (Gattex and Eohilia) under Takeda, where I executed 150+ model iterations that boosted campaign-led sales by +30% for Eohilia and +20% for Gattex. By automating data preprocessing, feature engineering, and validation pipelines in Python, I reduced model execution time by 80%, driving scalable and reliable solutions. Across every role, my goal remains consistent — to bridge business strategy and data science, collaborating cross-functionally to turn complex datasets into actionable insights that deliver measurable impact.
Analyzed fuel consumption data and implemented the SARIMA model, resulting in accurate forecasts that streamlined inventory management processes and reduced stockout occurrences by 15%. Automated reporting processes, reducing the time to generate key reports by 30%, enabling timely data-driven decision-making for senior leadership. Played a key role in cross-functional collaboration, contributing to strategic initiatives that improved customer satisfaction scores by 20%, while reducing operational delays by 12%.
Optimized Chatbot performance by analyzing user interactions to improve query resolution rates by 10%, reduce response times by 25%, which lead to overall user satisfaction. Processed large datasets for intent classification, boosting NLP model accuracy by 15%. Conducted A/B testing and predictive modeling to optimize chatbot workflows anticipating user needs.