YU XIE

Master’s student in Knowledge Management at NTU with over three years of product management experience at DJI, specializing in digital transformation. Demonstrated expertise in driving user-centric product strategies and leveraging data analytics to enhance user engagement. Proven track record of developing innovative solutions and streamlining processes to achieve impactful results aligned with organizational goals. Skilled in managing product lifecycle stages and executing initiatives within dynamic, global environments.

DJI Self-Service Knowledge Platform | 01/2022 – 07/2023

• Objective: Improve customer support efficiency by creating a centralized knowledge repository for internal and external use.
• Role: Led the end-to-end development of the platform, collaborating with engineering, design, and customer service teams.
• Actions:Analyzed fragmented support resources and identified gaps in accessibility and usability.
  Designed the platform structure to streamline resource navigation and retrieval for users.
  Partnered with UX designers to develop a user-friendly interface optimized for global audiences.
• Impact: Reduced support inquiries by 25%, saving operational costs and improving customer satisfaction scores by 15%.

Social Media Data Analysis for Marketing Optimization (DJI) | 04/2020 – 01/2022

• Objective: Enhance customer engagement and retention through data-driven insights.
• Role: Conducted data analysis using Python and Tableau to monitor user interaction patterns across DJI’s app and social media platforms.
• Actions:Analyzed engagement metrics from YouTube and WeChat Mini-Programs to identify trends and content preferences. Created interactive dashboards for internal teams to visualize real-time engagement data. Provided actionable insights that informed product feature updates and marketing campaigns.
• Impact: Achieved a 20% increase in user engagement and guided marketing teams in creating targeted campaigns aligned with customer needs.

Film Graph Database and User Recommendation System
Graduation Project | Nanyang Technological University (NTU) | 09/2023 – 07/2024

• Objective: Designed and developed a movie recommendation system and community platform using a graph database to enhance user engagement and content discovery.
• Role: Led backend development, database design, and recommendation algorithm implementation for an interactive web platform.
• Actions: 1. Constructed a movie knowledge graph using Neo4j, integrating datasets from Kaggle with over 45,000 movies and 480,000 user ratings.
  2. Implemented recommendation algorithms, including collaborative filtering and content-based methods, enabling personalized movie suggestions tailored to user preferences.
  3. Built Python-based data preprocessing pipelines to clean, structure, and merge large datasets, ensuring efficient integration into the Neo4j graph database.
  4. Developed a web interface using the Django framework, supporting real-time user interactions such as movie searches, ratings, and tagging.
  5. Conducted A/B testing of recommendation models, achieving a 20% increase in accuracy and improving overall user satisfaction with content recommendations.
• Impact: Delivered a scalable and user-centric platform that facilitated interactive exploration of movie connections while significantly improving recommendation precision and user engagement.