About

Rajasvi Vinayak Sharma is a skilled Data Scientist and Machine Learning Engineer with experience in developing end-to-end data science project pipelines. He is currently pursuing an MS in Machine Learning and Data Science at UC San Diego, specializing in Natural Language Processing (NLP). Rajasvi has relevant projects related to Anomaly Detection, Name Entity Recognition, Recommendation systems, and Deep Learning for NLP. Rajasvi has worked as a Data Science intern at NVIDIA, where he gained experience in Time-series Anomaly Detection models, Hypothesis A/B Testing, and Causal Inference. He developed a Time-series Anomaly Detection tool to alert about malicious activities in 1000+ categories across 10M+ gaming sessions, reducing response time from a few months to 1 week. He also improved in-place A/B test analysis by creating a tool to identify the most affected sub-population using causal inference ML models like S-Learner, T-Learner, Double ML methods, etc. Rajasvi built user engagement metrics using regression analysis and game completion modeling to identify and target disengaged users. He was able to track user’s local and absolute engagement while progressing in a game. Before graduate studies, Rajasvi worked for three years at Goldman Sachs’s Search Engineering team, building an internal natural language search engine. He gained experience in Big Data technologies, developing real-time streaming Big Data ETL pipelines, scalable ML models, and integration within the search engine infrastructure. Rajasvi is currently working as a Graduate Teaching Assistant for the course - Accounting Data Analytics under the supervision of Prof. Mario Milone at the Rady School of Management - UC San Diego. The goal of this course is to provide a basic understanding of recent technologies used in data analytics, machine learning, and more broadly artificial intelligence. Rajasvi has a Bachelor of Technology (BTech) degree in Electronics Engineering from Indian Institute of Technology (Banaras Hindu University), Varanasi. He is proficient in various technologies such as ML, Data Scientist, Research Scientist, Software Engineer, NLP, Big Data, Search, Recommendation system, test, Deep Learning, ETL, infra, Integration, Pandas, Pytorch, n-grams, Tensorflow, SQL, Reinforcement Learning, Databricks, HDFS, AI, Perceptron, CNN, language models, Python, Spark, Scikit, Redis, Hadoop, Kafka, Web, C++, Java, and Android. Rajas