Developed and maintained the US Bank onboarding web application using JavaScript, TypeScript, React.js, and supporting multi-tenant integration for clients such as US Bank, State Farm, Elavon, and Talech, contributing to an average monthly increase of 20k small business customers worldwide.
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Collaborated on the development of a no-code platform (UI-configurator), enabling over 20 teams at USBank to rapidly build and customize their web pages and workflows.
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Delivered to the USBank POS product (Talech) development, including ordering systems, merchant management systems, dashboard, and the new talech.com homepage using React.js.
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Implemented asynchronous data handling in web applications using Redux-Thunk and Redux-Promise as middleware to manage RESTful APIs with JSON Web Token (JWT) for user authentication.
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Enhanced code quality and reliability by implementing unit tests using Jest to improve testing coverage.
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Designed user-centric web interfaces compliant with A11y standards, employing semantic HTML5 and CSS3 to ensure adaptability and responsiveness while enhancing user experience.
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Managed CI/CD pipelines using Jenkins to facilitate multi-environment deployments (IT, UAT, Prod).
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Integrated third-party APIs such as Google API and Salesforce API to extend application functionality.
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Developed RESTful APIs using Java to enable seamless communication between front-end and back-end.
Cooperated in the design and development of Single Page Applications (SPA) using MERN Stack technologies (MongoDB, Express.js, React JS, Node.js) along with JavaScript, HTML5, CSS3.
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Implemented Life Cycle methods to handle various operations throughout the application.
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Created Responsive Web by using Bootstrap and CSS Media Queries, optimized CSS file using SASS.
COVID-19 and resident behavior data analysis and Machine Learning application
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Remotely connected to the CARC Advanced Computing Center to wrangle Large Mobility data by SQL.
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Extracted features and visualize interactive time series graphs and Choropleth maps by using R programming.
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Built support vector machine (SVM) as the classifier and used cross-validation to obtain the best model parameters.
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By using SVM model, classified city blocks according to their behavioral differences and identify correlation relationships between the census demographic data, mobility data, and COVID-19 infection data.
