Support recommendation strategy projects for the e-commerce platform, including assisting in product mechanism design and basic strategy optimization.
Analyze user behavior and traffic distribution in recommendation scenarios (e.g., homepage, search, feeds), identify issues, and propose data-backed improvement suggestions.
Work closely with data analysts and algorithm teams to monitor recommendation performance, conduct basic analysis, and support A/B testing.
Collaborate with cross-functional teams (e.g., product, operations, marketing) to understand business needs and help translate them into recommendation use cases or optimization ideas.
Conduct competitor analysis and industry research on recommendation systems and personalization trends, providing insights to support product iterations.
Assist in tracking key metrics (e.g., CTR, CVR, GMV contribution) and preparing reports to evaluate recommendation effectiveness.
Requirements
Pursuing a bachelor's degree or above in Computer Science, Data Science, Business Analytics, Information Systems, or related fields.
Strong interest in e-commerce, recommendation systems, and personalization technologies.
Basic understanding of data analysis concepts; familiarity with Excel/SQL/Python is a plus.
Good logical thinking and problem-solving skills, with the ability to break down problems and propose structured solutions.
Strong communication and collaboration skills, with the ability to work effectively in cross-functional teams.
Detail-oriented, proactive, and eager to learn in a fast-paced environment.
Prior internship or project experience related to data analysis, product management, or e-commerce is a plus.
Able to commit to a full-time internship for at least 3 months.
