Data Scientist

• Review and refactor existing data table structures, field semantics, and key/ID systems to resolve legacy issues such as “one field with multiple meanings”
• Design and drive a unified data model and metric definitions; establish a company‑wide data dictionary and data standards
• Partner closely with engineering to participate in data warehouse modeling and data pipeline (ETL/ELT) design, improving data quality and maintainability
• Own the overall methodology and implementation path for A/B testing and other online experiments across the company
• Design experiment pipelines, including traffic allocation, tracking/instrumentation strategy, data collection, data storage, and analysis workflows
• Develop standardized experiment analysis frameworks and reusable templates, including core metrics, significance testing, sample size estimation, and evaluation guidelines
• Deeply engage with core business lines and define problems and key metrics starting from product and business goals
• Based on the unified data system, provide structured data analysis and experiment recommendations to product and business teams
• Use data and experiment results to identify growth opportunities, product optimization directions, and potential risks, and clearly communicate findings to non‑technical stakeholders
• Promote data naming conventions, field definitions, and tracking standards, and ensure their adoption across the company
• Establish and maintain data quality monitoring mechanisms to detect and fix data issues
• Document and socialize internal best practices related to data and experimentation, helping to build a strong data culture and improve overall data usage efficiency.

Data Scientist

Data Scientist I, Real World Data Science

Data Scientist II

Data Scientist

Junior Data Scientist

Senior Data Scientist, Product Growth