About

Harsh Sarda is a Senior Applied Data Scientist with a theoretical understanding of ML/DL algorithms and hands-on experience in building production-ready systems from scratch. He has worked on different kinds of use cases like unsupervised anomaly detection, loan underwriting, risk-based pricing, time series forecasting, Seq2Seq modeling, image classification, etc. He has handled problems in various domains like FinTech, RegTech, Insurance, Hospitality, Healthcare, etc. Harsh is currently working at Tookitaki, where he is part of the Data Science Research team responsible for building Anti-Money Laundering solutions. He has expertise in Data Science Solution Design, Content-Based Recommendations, Unsupervised Anomaly Detection, Synthetic Data Creation, Clustering, Big Data Pipelines, and Dynamic Feature Creation/Selection. Prior to Tookitaki, Harsh worked at JP Morgan as a Data Scientist, where he created Interpretable Machine Learning Solutions for products in the Wholesale Credit Banking Business. He has experience in Client Rating Downgrade Prediction, Time Series Forecasting, and XAI (Shapley, Surrogate Decision Tree, etc.). Harsh holds a B.Tech & M.Tech (Dual Degree) in Chemical Engineering from the Indian Institute of Technology, Delhi, and is currently pursuing a PG Level Advanced Certification Programme in Deep Learning Foundations and Applications from the Indian Institute of Science (IISc). He also holds a Senior Secondary School degree in PCM from Shri Gujarati Samaj B.Ed. College, Indore, and a Secondary School degree from Sri Satya Sai Vidya Vihar, Indore. Harsh has a diverse Tech Stack, including Research Scientist, Data Scientist, ML, Deep Learning, NLP, Scikit, Big Data, Python, Text Classification, P2P, Random Forest, and AI. He has been ranked #28 on Analytics Vidhya DS platform. Harsh has 4.37 years of relevant experience in the field of Data Science.