Senior Data Scientist, Analytics (Mandarin Required)

About the role

A rapidly scaling consumer internet platform, connecting hundreds of millions of users daily across content, community, discovery and commerce, is hiring a Senior Data Scientist for its Singapore team. The role sits at the intersection of data analytics, product analytics, decision science and business strategy, working closely with Product and Business teams to turn quantitative analysis into product and strategic decisions. Fluency in Mandarin and English is mandatory.

Key responsibilities

• Lead complex data analysis to support product, commercial and strategic decisions
• Analyse user behaviour, product performance and business trends to find growth opportunities and diagnose problems
• Build measurement, quantification and attribution frameworks to measure the true impact of initiatives
• Identify the drivers behind changes in key metrics and turn findings into actionable recommendations
• Build and evolve business data systems, metrics and analytical frameworks
• Combine internal platform data with industry data, market perspectives and external trends
• Partner with Product, Business and other stakeholders to influence short-term execution and long-term direction
• Use modern AI tools to build and improve end-to-end analytical workflows

Required profile

• 5-10 years of experience in data analytics, product analytics, data science, business analytics, decision science or a closely related quantitative discipline
• Bachelor's degree or above in Computer Science, Statistics, Mathematics, Economics or another quantitative discipline
• Strong experience in consumer internet, technology or other data-intensive product environments
• Experience influencing product strategy, experimentation, growth, monetization or commercial decisions
• Fluent Mandarin and English, able to discuss complex analytical topics with stakeholders in China in Mandarin

Required skills

• Quantitative, statistical and analytical foundations
• Measurement, attribution and impact analysis
• Building metrics, analytical frameworks and reusable data capabilities
• Stakeholder management and clear communication to technical and non-technical audiences