About

Prathit Pannase is a skilled software developer with a passion for software engineering. He is currently pursuing a Master's degree in Information Systems Management at Carnegie Mellon University. Prathit has over 4 years of experience in developing distributed systems, high performing web servers, and working with REST APIs in Java and Python. He has also built ETL pipelines in Scala and Spark, and has experience working with Kafka, Samza, Hadoop, MapReduce, Docker, and Kubernetes. Prathit has worked on multiple cloud platforms, including AWS, Azure, and GCP. He has developed projects on AWS, such as EC2, RDS, Load Balancer, ECS, EKS, Lambdas, and Fargate. On Azure, he has worked with Functions, Stream Analytics Job, EventHub, Triggers, and Blob Storage. On GCP, he has experience with Dataproc, AI Platform, Functions, and NLP APIs. Prathit is also experienced in machine learning, including neural networks, SVM, logistic regression, feature engineering, data cleaning, and analytics. He has worked with databases such as MySQL, HBase, MongoDB, Redis, and Neo4j. Currently, Prathit is working as a Software Engineering Intern - Data Analytics at Samssara Capital Technologies LLP. He has worked in the algorithmic trading domain and has developed a software in Java that compared multiple trading strategies and their performances. Prathit has also reduced the manual execution time by programming a Java system for automating daily tasks like calculating slippage and PnL (Profit and loss). He has analyzed stock data for developing mid-frequency trading strategies, which resulted in increased revenue. In the past, Prathit has worked as a Software Engineer - Data Analytics and a Software Engineering Intern - Data Analytics at Samssara Capital Technologies LLP. He has built a software in RStudio to perform backtesting on high-frequency trading strategies and has implemented machine learning algorithms in R for weekly predictions of what stocks to trade on global financial markets, thus increasing the profitability of the strategy. Prathit has also created a Python framework to test and evaluate multiple trading strategies and has designed a high-frequency trading strategy and developed a Java platform for executing the live trades. Prathit's tech stack includes software engineering, infra, AWS, SVM, Neo4j, ECS, AI, NLP, Spark, MapReduce, Redis, Kubernetes, Docker, ML, neural networks, MySQL