Responsibilities
1. Cooperate with multiple e-commerce business departments to recommend products, algorithms, and operate multiple e-commerce business departments. Through data analysis, data mining, experimental analysis, change attribution, feature construction, etc., assist the business in gaining insights into user strategies, content product supply, traffic distribution and other directional issues, bring incremental awareness to business development, and work with the business to optimize the e-commerce recommendation system, improve user experience, and create value for users 2. Construction of the e-commerce recommendation indicator system: Based on the core strategic goals of the business, formulate and improve the e-commerce recommendation indicator system, plan and build business indicator data and data products, complete core business indicator change attribution, provide decision-making support for the business and management, and realize data productization 3. Experimental engineering: Participate in the entire process of AB experiments such as experimental design, experimental change attribution, experimental effect evaluation, and experimental drill-down analysis, provide optimization suggestions for the iteration direction of the recommendation strategy through experimental analysis, standardize the construction of the experimental evaluation system, assist the business in formulating experimental evaluation indicator groups, and formulate scientific indicator evaluation methods 4. Recommendation strategy analysis: Based on business strategic goals and understanding of e-commerce business, formulate a logical and clear analysis framework, write professional analysis reports, clearly locate business development issues through analysis, and provide incremental insights for business development to guide business development direction 5. Feature mining: Through statistical learning, machine learning and other modeling methods, mine user behavior patterns, content, product feature value, content, product supply clues, assist in optimizing recommendation algorithms, mine algorithm-driven business growth points, and promote the implementation of data products and technologies 6. Methodological precipitation and innovation: Organize relevant teams to conduct training on data product concepts, skills, and tools to promote digital operations of business departments.
Qualifications
1. Work experience related to data analysis, mining, and modeling. Applicants with experience in e-commerce search, recommendation, and advertising data are preferred. Computer, statistics, and mathematics majors are preferred. Applicants with a foundation in machine learning algorithms will receive extra points 2. Master basic data analysis methods, have some experience in implementing data into business, and have the ability to write professional analysis reports 3. Have relatively rich experience in feature engineering, user behavior modeling, etc., be able to turn abstract problems into concrete models based on actual business scenarios, and ultimately provide data-driven products and insights, and influence the tracking records of product and business decisions 4. Have experience in using SQL, Python, etc. for data analysis. Applicants with modeling experience will be selected 5. Passionate about data science, possess a sense of ownership, have excellent communication and expression skills, and strong coordination and promotion capabilities.
