Arjun Nair

Software Engineering Co-op

Sun Life Financial•  January 2023 - April 2023•  Toronto, ON, Canada

- Enhanced the Client Experience Platform (CXP) by adding and updating fields in domain services and configuring Kafka topics and tables, leading to a 35% improvement in real-time access to key client data. - Optimized acceptance testing using Docker and Kubernetes, reducing test time by 30% and increasing deployment frequency by 25%. - Developed configuration files and custom keywords within the ROBOT testing framework to maintain 100% test coverage and reliability.

Software Developer Co-op

Tulip Retail•  May 2022 - August 2022•  Toronto, ON, Canada

- Enhanced [Well.ca](http://well.ca/)’s user interface by implementing key front-end features and accessibility improvements, ensuring better usability and significantly improving the user experience for 100,000+ customers. - Developed and integrated a multi-courier delivery tracking system using PHP, SQL, and JavaScript, boosting customer satisfaction and retention by 20%. Streamlined implementation through direct liaison with couriers and clients.

Software Engineer Intern

Adknown•  September 2021 - December 2021•  Guelph, ON, Canada

- Designed and implemented a component library with React and Material UI that standardized UI elements across the application; this library is now utilized by over 10 developers across 2 teams, improving consistency and efficiency across projects. - Authored an easy-to-navigate guide for non-technical staff, facilitating seamless tool integration; efforts yielded a 25% reduction in onboarding errors and enhanced collaboration across departments by 35%.

Data Science Intern

Group 42•  September 2020 - March 2021•  Abu Dhabi, United Arab Emirates

- Built a web application for medical insurance claims using Python (Streamlit, pandas, NumPy) and HTML/CSS, which accurately predicted claim outcomes. This project was highly praised by management and clients for its accuracy and impact on decision-making. - Engineered a recommendation system using a Neo4j graph database and custom Python and Cypher queries, improving data retrieval efficiency by 40% for medical professionals. - Created an interactive D3.js visualization tool for medical treatments, automating dataset generation and reducing manual entry time by 70%.