• Developed frontend ios mobile application with SwiftUI, constructed the MVVM model ensure the scalability and reusability, improved development efficiency by 30%• Facilitated the API documentation by Swagger, tested through Postman ensure the seamless functionality• Developed and maintained a scalable Azure database for 5TB+ health data, achieving 99.9% uptimeSourced varied data, shaping personalized health recommendations for 50K users• Led 5+ informant interviews and crafted a Figma mobile app prototype, boosting user engagement by 30%

• Facilitated the development of marketing campaign WeChat embedded programs• Designed 4 user-centric prototypes using Sketch, transferred requirements into workflow with 95% positive feedback• Collaborated with engineering and client team to define technical requirements and dependencies, design system architectures through UML; clarified data compliance to overseas clients• Implement product specifications involving complex algorithms, managed developing life cycle(PMLC) and tracked 10+ defect cases via Jira• Preprocess a 10GB customer dataset, leveraging CRM tools to analyze and enhance customer profiles, directly contributing to a more personalized customer experience and a 15% increase in customer satisfaction

• Developed a comprehensive integration plan resulting in a new requirement specification that addressed diverse HR business needs across user roles• Led UX and A/B testing initiatives in 7 countries, enhancing phrase consistency and clarity by 30%, while also collecting feedback to address cultural sensitivities and nuances specific to each language• Employed data-driven feedback analysis using Google Analytics and custom metrics to guide product enhancements, leading to a 15% improvement in customer satisfaction ratings• Established measurable objectives for iterative improvements (E.g. 30% increase in user engagement)，integrating OKR framework to quantify project impacts

• Processed e-commerce data, implemented database for 50k clients using SQL queries, Python NumPy, Pandas modules to perform data cleaning resulted 27.5% increase on number of clients• Optimized data analysis by transforming 50GB of images into a dataset for preference analysis, reducing interpretation time by 15%, trained YOLOv3 models for efficient image classification• Ensured data integrity and interpreted data with Python(E.g: statistical inference, regressions), contributing to a 30% increase in client retention rate

• Conducted testing for Role-Based Access Control (RBAC), ensuring accurate content access permissions for 1k+ users• Wrote queries for extracting targeted data in Oracle, executed 50+ test cases for data migration, tracked bugs on Jira, documentation on Confluence• Wrote template for automated data-converting validation, implemented regular expressions for email format checking, ensuring all email addresses conformed to standard formats