Vipin Dileep

Dynamic and results-driven Branch Manager at Bank of Baroda with over 8 years of managerial experience and a passion for driving innovation through artificial intelligence (AI) and data analytics. Specialized in AI-driven solutions for the banking sector, with a unique blend of leadership, technical expertise, and analytical skills. Proficient in Python, Generative AI, data science, and natural language processing (NLP), with a proven track record in team management, project execution, and delivering transformative AI strategies. Certified in Artificial Intelligence & Data Science from IIM Kozhikode.Actively pursuing roles to contribute to the development and deployment of cutting-edge AI solutions in a global financial environment.

• Successfully deployed AI models to optimize branch operations, saving over 500 hours annually.
• Designed end-to-end machine learning pipelines for customer sentiment analysis and personalized service recommendations.
• Trained cross-functional teams on AI tools and methodologies, fostering a culture of innovation within the branch.
• Managed multi-million-dollar portfolios while integrating advanced AI analytics to drive decision-making.
• Conducted thorough credit and risk assessments, significantly reducing loan default rates.
• First runner up in Baroda Gyani Quiz Competition 2023

• Project-Risk Analytics in Banking and Financial Services: Leveraged machine learning and statistical models to predict and mitigate risks in msme loans.
• Recommendation System for Book Ratings: Built a scalable recommendation system using collaborative filtering, addressing memory issues with a sparse matrix representation.
• Sentiment Analysis for Product Reviews: Developed a text classification model using TF-IDF and NLP techniques to categorize user feedback.
• Recommender Systems: Built systems for business and retail applications, including simple ranking, knowledge-based, and content-based approaches.
• Association Rule Mining: Implemented a rule-mining system to uncover patterns in transactional data, enhancing business decision-making.
• Collaborative Filtering: Designed and deployed collaborative filtering systems for personalized recommendations.
• Generative AI for Business Use Cases: Designed and implemented customized Gen AI models for finance, digital marketing, coding, and product management.
• Evolutionary Computing for Optimization: Applied genetic algorithms, particle swarm optimization, and ant colony optimization for clustering and classification tasks.
• Text Analytics: Conducted sentiment analysis, sarcasm detection, topic modeling, NER, text summarization, and conversational AI demonstrations.
• AI-Driven Insights: Combined analytics, experimentation, and algorithms to deliver actionable recommendations for business growth.

• Artificial Intelligence & Data Science – IIM Kozhikode
• Digital Transformation & Artificial Intelligence Applications in Banking – NIBM Pune
• CAIIB AND JAIIB

• Hands-on training in Generative AI, prompt engineering, and advanced deep learning techniques.
• Regular participation in AI conferences and workshops to stay updated on cutting-edge technologies.