• Analyzed business needs and designed a platform for researchers to optimize workflow efficiency and user experience• Designed highly available and scalable Amazon Web Services architecture for platform infrastructure• Implemented and deployed the Serverless backend APIs using AWS AppSync GraphQL API• Defined data model and deployed the NoSQL database by AWS DynamoDB hosting 50,000+ samples from hundreds of studies• Developed front-end webpages hosted on S3 bucket with React, Redux and Material UI for data uploading, validation, and dynamic cascaded filtering• Implemented the user authentication and group-based authorization with lambda function, amplify and Cognito to achieve permission control• Documented APIs with OpenAPI 3.0 for internal developers and external users to test and execute APIs• Implemented a comprehensive Continuous Integration/Continuous Deployment (CI/CD) pipeline to integrate automated testing and update schema file on each push by using GitHub Actions

• Developed a platform for 10+ kinds of data analysis and visualization by RShiny, HTML, CSS, and JavaScript• Designed and developed a workflow with Snakemake for pre-processing microbiome sequencing data by Qiime2• Customized script to analyze and visualize result in R language, Python and Bash for secondary analysis• Trained the predictive machine learning algorithm on experimental data in Python scikit-learn• Hosted a workshop with 50+ customers for improving the workflow, analyzed requirements and defined roadmap

• Created a web crawler to collect customers text reviews by using Python and Scrapy• Used MongoDB to store reviews and recommendations from 4 major E-commerce shopping and sharing platforms• Analyzed reviews in Python by a Chinese text analysis package Jieba and a Natural Language Processing (NLP) package Spacy to explore business values behind reviews and recommendations data• Developed reproducible reports that meets marketing objectives by using Ipython notebook