Profile
Master's student in Information Management & Business Analytics at The Chinese University of Hong Kong, Shenzhen (QS Top 50).
Product Manager with internship experience at Tiger Brokers (derivatives trading) and Hupu (user research & growth).
Skilled in translating user insights into product solutions, with a strong focus on fintech UX, AI product design, and data-driven decision making.
IELTS 7.0, fully English-taught throughout undergraduate and graduate studies.
Education
M.S. in Information Management & Business Analytics
2025.09 - 2027.08 at The Chinese University of Hong Kong, Shenzhen (QS Top 50)Core courses: Systems Design & Analysis, Project Management, Big Data Analytics, Web Analytics, Database Management, Mathematical Analysis
B.S. in Information Management & Information Systems
2021.09 - 2025.06 at Southwestern University of Finance and Economics (Project 211)Delaware Data Science College
Experience
Product Manager Intern — Derivatives Trading
2025.11 - 2026.03 at Tiger Brokers (Beijing Yixinxiangshang Technology), Product Department
- Order Search UX Redesign: Users could only search orders by exact ticker code, causing frequent support tickets. Analyzed customer complaints and identified the core mental model as "options OF what I bought" rather than "what options I bought." Designed a 3-layer solution: filter optimization + fuzzy Chinese/English name search + derivative-underlying asset association. Daily PV increased from 24K to 28K, related complaints dropped to zero.
- HK Stock Options Paper Trading (0-to-1): Designed simulated matching logic for both real-time and delayed market data scenarios. Benchmarked against Futu and Interactive Brokers. Post-launch achieved 100+ weekly simulated trades, creating a complete learn → practice → live trading path for new users.
- Core Trading UX Consistency Governance: Identified that 3 order pages × 2 platforms = 6 inconsistent interaction standards. Unified interaction specs across all product categories. Projected feature retention rate improvement from 28% to 30%.
User Research Intern
2024.12 - 2025.04 at Hupu (Shanghai Kuanghui Network Technology), User Research Center
- Off-Site Content Distribution Platform: Led the design of an automated content distribution system integrating task publishing, AI-powered content production, channel distribution, data monitoring, and auto-settlement. Designed a "base + performance" dual-incentive model for scalable distribution.
- Content Production Strategy: Built a data-driven + editorial topic selection mechanism. Leveraged AI tools for automated content production, supporting 6,000+ pieces distributed across 500+ channels within 24 hours.
- User Growth Results: Single campaign published 3,288 pieces of content, generating 12.64M impressions and 8,449 effective new-user search referrals, validating scalable acquisition feasibility. Trial run achieved 10,000 new users per week.
Projects
Khrushchev Simulator — AI-Driven Historical Strategy SLG
2026.03 (Independent Project)
- Built a core loop of "intelligence generation → natural language negotiation → intent parsing & numerical settlement → world state emergence." Players negotiate among 5 factions and 31 characters through real dialogue, supporting 10 endings.
- Completed model selection based on role-play capability, Chinese quality, and token cost. Defined 3 AI metrics (numerical overflow rate, instruction compliance, character consistency) to drive prompt iteration. Overflow rate: frequent → zero; compliance: 85% → 95%+.
- Designed "presentation layer AI generation + logic layer hard numerical hosting" separation architecture to mitigate hallucination risks. Converted prompt injection into immersive NPC defiance/questioning experiences.
- 5-version closed beta with 5 core strategy gamers. Average 20+ rounds per session, all players voluntarily started a second playthrough.
Skills
- Office Suite
- Figma
- Axure
- SQL
- Python
- R
- Git
- Prompt Engineering
- Harness Engineering
- Data Analysis
- User Research
- Competitive Analysis
- Product Design
- IELTS 7.0