Job Responsibilities:

1. Participate in the design of A/B experiments and scientific evaluation mechanisms to guide product and strategy decisions in various business scenarios and enable rapid business iteration;

2. Deeply involved in the underlying mechanism development of A/B testing systems, attribution systems, anomaly detection systems, etc., and provide professional data science support;

3. Gain in-depth understanding of business needs and provide support and guidance for experiment analysis, anomaly attribution, and other data analysis tasks;

4. Explore new experimental methods and analysis techniques using causal analysis, machine learning, and other technical means to continuously improve product capabilities.

Job Requirements:

1. Bachelor's degree or above in statistics, applied mathematics, econometrics, operations research, computer science, or related STEM or business fields (preferred);
2. Solid foundation in statistics, with a strong interest and research spirit in causal inference and experimental science;
3. Familiar with Hive, Hadoop, big data computing frameworks, proficient in SQL and Python, with more than 2 years of experience in data analysis, data mining, or machine learning projects preferred;
4. Good foundation in statistics, probability theory, and experimental design; strong data analysis and visualization skills; experience in A/B testing and attribution analysis is preferred.