Full Stack - Payments Risk Foundations

• Programming Language (Backend)- Go, Golang, RubyonRails, Python

• Data- MongoDB, DynamoDB, Snowflake, Kafka, Databricks, Airflow

• Programming Language (Frontend)- ReactJS, React Native, TypeScript, Next.js, ReactDOMServer, GraphQL

• Other Technologies- Redis, S3, AWS, EC2, Docker, Kubernetes, Protocol Buffers, gRPC, Github, RESTful APIs, Microservices,

• Analyzed diverse datasets using statistical and machine learning techniques to identify statistical arbitrage opportunities in US, European, and Asian equity markets on WorldQuant Websim

• Developed 50+ equity long/short strategies using Python and proprietary in-house programming language, achieving Median Sharpe ratio of -2.1, median annualized returns - 7.2%, median maximum drawdown - 1.5%

• Spearheaded the design and development of Advanced Bug Reporting Tool using React.js, Tailwind CSS, Material UI, JavaScript, and TypeScript for the frontend, and GraphQL and Node.js for backend interactions. Revamped entire Sprinklr’s bug-tracking cycle

• Boosted entire user feedback precision by 50% by implementing advanced features like screenshot commenting, drawing utilities, and video capture to boost user interaction and significantly optimize the bug-tracking process.

I was awarded the MITACS Global Research Internship / Scholarship for fully funded research in Canada during Summer 2023 at Toronto Metropolitan University, Ontario, Canada.

• Played a pivotal role in the design and coding of the Lung Ultrasound GUI Application, utilizing Python to automate the detection of lung ultrasound patterns.

• Translated medical concepts into a user-friendly software application, utilizing HTML & CSS to enhance the user interface for doctors & clinicians.

• Worked with state-of-the-art models & Deep Learning Algorithms for real-time pattern recognition for detecting lung ultrasound patterns.