Murali Mohana Krishna Dandu

Murali Mohana Krishna Dandu is a Senior Data & ML Scientist with over 7.5 years of experience in AI/ML, specializing in NLP, recommender systems, and end-to-end ML lifecycle management. At Walmart, he developed advanced recommender models and improved cross-category recommendations, achieving significant boosts in performance metrics. His previous roles include enhancing search algorithms at Wayfair and deploying biomedical NLP solutions at Sumitovant Biopharma. With a Master’s in Data Science from Texas Tech University and extensive experience with major clients like Walmart and Home Depot, Murali has a proven track record in delivering impactful, scalable AI solutions. Murali Mohana Krishna Dandu is a seasoned data science and machine learning expert with over 7.5 years of experience leading and executing AI/ML projects across diverse industries such as e-commerce, retail, advisory, and biomedicine. He has deep expertise in Natural Language Processing (NLP), recommender systems, and the end-to-end machine learning lifecycle. His technical skills encompass languages like Python, R, SQL (BigQuery, Hive), and PySpark, as well as frameworks such as PyTorch, TensorFlow, Keras, HuggingFace, and Scikit-Learn. Murali also has substantial experience with Generative AI (OpenAI, LangChain) and cloud platforms like GCP (Vertex AI, Dataproc) and AWS (SageMaker). Currently, as a Senior Data & ML Scientist at Walmart, he has worked on innovative projects like developing dual-transformer-based sequence recommendation models for cart-based suggestions, enhancing retrieval models using purchase behavior, and creating cross-category recommendations. His work has led to measurable improvements, such as a 5% increase in cart page Add-to-Cart (ATC) and significant growth in GMV. Additionally, he has implemented knowledge graphs using OpenAI and LangChain for various objectives, including cross-selling and persona development. Previously, as an ML Engineer Intern at Wayfair, he made improvements to the company's neural retrieval model, resulting in an estimated search click-through rate impact of $500K annually. His early work in biomedical NLP, particularly with Sumitovant Biopharma, involved fine-tuning state-of-the-art BERT models for tasks like multi-label classification and relation extraction. Murali has also contributed to multiple high-impact projects at Tredence Inc., where he led the development of intelligent delivery promise systems for e-commerce platforms, achieving significant revenue lifts. His academic background includes a Master of Science in Data Science from Texas Tech University, where he achieved a perfect CGPA of 4/4. In addition to his practical experience, Murali has been involved in impactful academic projects, such as building a recommendation system for Google Local and enhancing retail stockout identification systems using YOLOv5 and RCNN. He has authored publications in top conferences, including ECML PKDD 2021 and the AMIA 2022 Informatics Summit, and holds patents related to his work at Walmart. Through his career, Murali has consistently demonstrated his ability to drive innovation and lead teams to successful project delivery, making him a highly valuable asset in the AI/ML space.