About

Vipul Gaba is a highly experienced Machine Learning (ML), Data Science, and Analytics professional with over 13 years of experience. He is currently working as a Machine Learning and Data Science expert at Airtel Digital, leading the ML and AI charter across the entertainment division, including Wynk Music and Xstream. Vipul is responsible for implementing ML and AI solutions for personalization and recommendation, ML-powered search, growth and engagement, and catalog quality improvement, among others. He has a strong background in classical ML, deep learning, natural language processing, graphs, and big data processing techniques. Vipul is a graduate of NIT Kurukshetra with a B.Tech in Electronics and Communication Engineering and has consistently been at the top of his class. He has a strong leadership background, with cross-functional technical and business stakeholder management experience in healthcare, eCommerce, and entertainment/OTT domains. Vipul is also leading and mentoring a team of Data Science and ML professionals supporting various organizational verticals. In his previous role as Senior Manager - Data Science at guenstiger.de gmbh, Vipul developed a paid search traffic acquisition model, implemented text classification models, created a binary class propensity model, and developed a hybrid recommendation engine, among others. He has also worked at ZS Associates as a Business Associate, where he worked with Fortune 500 pharmaceutical clients in designing incentive plans and measuring sales force effectiveness. Vipul possesses an extensive tech stack, including ML, Data Scientist, NLP, AI, deep learning, search, SQL, Sagemaker, AWS, big data, CNN, Python, recommendation systems, text classification, XGBoost, Docker, neural networks, hyperparameter, word2vec, corpus, Apache Hive, infra, Keras, Scikit, product manager, TensorFlow, Pandas, Flask, and Pytorch. Overall, Vipul Gaba is a highly skilled and experienced Machine Learning and Data Science professional with a proven track record of delivering effective solutions across a range of domains.