Abhinav Sood is a Senior Data Scientist with 13 years of experience applying machine learning and big-data engineering to finance, compliance, and healthcare-adjacent domains from Toronto. He has built production-grade Spark and Python pipelines that reduced manual credit adjudication by 75% and cut fraud losses by millions, and has implemented scalable unsupervised and deep-learning solutions for anomaly detection and document OCR. Comfortable across the stack—SQL, Spark, Hadoop, Keras, Docker—he blends research-minded experimentation (topic modeling, transfer learning) with practial delivery for enterprise systems. His background spans consulting and product environments, from anti-money-laundering detection at Oracle Financial Services to research in human-robot interaction, reflecting a knack for translating academic techniques into business impact. Notably, he has repeatedly deployed fast, Spark-native implementations of complex algorithms (HBOS, random forests, LDA) to handle truly large datasets in production.
14 years of coding experience
9 years of employment as a software developer
IK Gujral Punjab Technical University
Master’s Degree, Computer Science, Master’s Degree, Computer Science at Professional Master's Program in Big Data at Simon Fraser University
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