About

Juan Pablo Equihua Linares is a highly skilled Data Science Researcher, PhD student, and KTP Associate with a total of 5.78 years of relevant experience. He is currently working as a Data Science Researcher KTP Associate at profusion, where he has conducted detailed research and developed end-to-end machine learning, deep learning, and intelligent systems to predict successful marketing campaigns. He has improved prediction performance by 30% and reduced computational costs by 400% for predicting the propensity to purchase and CLV. Juan has also implemented a recommender system capable of identifying which items customers are most likely to be interested in the near future, and developed an e-mail engagement score to increase customer retention and brand engagement by 20%. In addition, he has supervised MSc Data Science dissertations related to AI and recommender systems. Prior to his current role, Juan worked at the University of Essex as an MSc Data Science student, where he researched and developed deep learning architectures to approach multiple data science and machine learning tasks with analytical models. He also developed deep learning models in sentiment analysis and text classification for a growing news host in the UK. Additionally, he mastered machine and deep learning techniques to work and predict raw input data such as images, text, and videos. Juan has also worked as a Fraud Prevention Specialist at Buró de Crédito, where he managed a multidisciplinary team to implement the biggest machine learning tools for fraud prevention in Mexico. He coordinated analytics, IT, and sales teams to implement two fraud prevention models used by top banks, retailers, and automotive companies in Mexico. He designed and presented ad-hoc analytic models and KPIs to detect fraud applications in credit loans and reduced fraud to almost 0% for given patterns. Juan's education history includes a Doctor of Philosophy - PhD in Data Science from the University of Essex, a specialization in Recommender Systems from the University of Minnesota, an MSc Data Science from the University of Essex, and a BSc Actuarial Sciences from the Universidad Nacional Autónoma de México. Juan has a strong tech stack, including expertise in Data Science, Research Science, Deep Learning, Sentiment Analysis, ML, AI, Text Classification, Python, Elastic Search, Search, Web, and Neural Networks.