About

Melwin James Poovakottu is a Director of Data Science at Pixalate with over 8 years of experience in ML, data analysis, and deep learning. He has a strong background in enterprise-level big data and data science implementations, and holds a Master's Degree in Data Science from the University of California, Berkeley. In his current role, Melwin leads a team of data scientists and analysts to develop novel bot detection and fraud prevention algorithms, as well as analytics products to support marketing and customer support. He has developed various anomaly detection, bot detection, and fraud prevention models using statistical techniques, deep learning, clustering, and graph theory. Melwin has also developed NLP models to determine apps targeting and violating children's privacy rights, as well as entity extraction models to unify and label free-form text into media entities. Prior to his current role, Melwin worked as a Data Scientist at Pixalate where he led various web seminars focusing on publisher quality. He also worked as a Senior Technology Analyst (Data Science and Big Data) at ZS Associates, where he was a member of the team that won the BioIT-2016 Award for their data science platform for the pharmaceutical industry. Melwin has experience performing statistical analysis and causal inference using multivariate analysis, inferential and descriptive statistics, and experimental design. He has developed multiple machine learning and deep learning models such as OLS regression, gradient boosted machine, NMF, naive Bayes, and convolutional neural nets on multiple projects in the clinical trials and product development space. Melwin's education includes a Master's Degree in Information and Data Science from the University of California, Berkeley, a Master's Degree in Engineering Management from the University of California, Irvine, and a Bachelor of Engineering in Electronics and Telecommunications Engineering from the University of Mumbai. Melwin's tech stack includes expertise in data science, deep learning, SQL, ML, naive Bayes, big data, research scientist, Python, NLP, Scikit, Tensorflow, web, Spark, sentiment analysis, Databricks, Hadoop, and Apache Hive.