Responsibilities
The commerce data science team aims to maximize the efficiency of commerce transactions through quantitative techniques such as mathematical statistics and machine learning. At the same time, we are committed to building a more diverse, inclusive, candid and efficient working atmosphere. We sincerely invite excellent data scientists to join us in building a first-class commerce platform.
About the Role
We're looking for a highly motivated Data Scientist to join our team and drive scalable, data-driven decisions across our SEA commerce operations. In this role, you'll use advanced analytics, experimentation, and modeling to uncover insights and develop systems that power strategic decisions across ecommerce growth, supply / product optimization, seller success, and many more.
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You'll work alongside operation / business, marketing, product, user growth leaders to design and implement high-impact solutions. Your work will directly influence business strategy and operational efficiency across our commerce platform.
In this role, you will
1. Leverage advanced statistical and machine learning techniques to solve complex business problems across marketplace efficiency, seller acquisition, and ecosystem health;
2. Design and implement rigorous A/B tests and causal inference studies to inform strategic decisions and product iterations;
3. Deeply participate in the daily operations of international e-commerce business, understand business logic and requirements, translate business logic into usable data analysis frameworks and indicator systems, and be responsible for defining and iterating the scope of core indicators;
4. Partner with cross-functional teams (business / operations, product, data engineering, marketing) to define metrics, monitor performance, perform attribution analysis and build scalable data solutions;
5. Drive exploratory analysis to identify key trends, patterns, and opportunities for growth in SEA markets, and present findings to stakeholders.
Qualifications
Minimum Qualifications:
1. 3+ years of experience in data science, quantitative research, or applied analytics, ideally in a tech-driven environment;
2. Strong command of SQL and proficiency in Python or R for data analysis, modeling, and scripting;
3. Deep expertise in at least one of the following: Causal inference and experimental design (e.g., A/B testing, uplift modeling, treatment effect modeling), Predictive modeling and machine learning (e.g., XGBoost, regression, classification)
4. Optimization and simulation (e.g., decision systems, pricing, supply/demand balancing);
- Solid foundation in statistics, data structures, and algorithmic thinking.
- Possess a knowledge framework for building data indicator systems, with prior experience in constructing indicator systems for large company;
- Strong communication skills and the ability to translate complex findings into clear, actionable insights for both technical and non-technical audiences;
Preferred Qualifications:
1. Experience in e-commerce or online marketplaces;
2. Experience working with large-scale experimentation systems;
3. Exposure to international markets or working on global operation teams.