Responsibilities
1. Focusing on the core propositions related to content ecology, based on data science and statistical theory, cooperate with students of international short video content ecology related products and strategy algorithms to explore the space for improving user experience from an ecological perspective 2. Focusing on the feedback from the ecological questionnaire, based on statistical theory correction and revision, capture user personalized signals and platform risks 3. Starting from the negative risks of the content ecology, design and balance the multi-business traffic framework starting from the positive experience of the content ecology, suggest indicators to guide the positive content experience 4. Explore the opportunities and risks of content ecology through quantitative analysis, statistical modeling, causal analysis, etc. build unbiased indicators and give feasible suggestions for content ecology strategy iteration.
Qualifications
1. Postgraduate degree, statistics, applied mathematics, operations research, economics, computer science, data science and other related majors, solid statistical foundation, familiar with A/B experimental evaluation system and sampling theory, build unbiased quantitative indicators to drive business goals 2. Master the basic capabilities and tools of mathematical sciences such as machine learning models, causal inference, prediction, optimization, etc., and be proficient in using SQL to complete data extraction and analysis be proficient in using at least one data analysis language such as Python 3. Have a good sense of product and structured thinking, be able to transform analysis results into business decisions, be good at analyzing and solving problems, have good cross-team communication and collaboration skills, and be passionate about challenges 4. Candidates with academic experience, recommendation algorithms, and analysis experience related to content ecology will get extra points.
