Machine Learning Engineering Manager - Global E-commerce (SEA)

About the Team
The Global e-commerce team is a content e-commerce business utilizing international short video products as carriers. Our aim is to become the preferred choice for users seeking to discover and purchase affordable, high-quality products. We provide users with tailored, vibrant, and efficient consumption experiences while enabling merchants to access robust and dependable platform services in various scenarios, such as live e-commerce and short video content e-commerce. Our vision is to make affordable and high-quality products easily accessible, enhancing the quality of life for all. We are actively seeking Tech Lead Managers to contribute to our team's growth and product success.

The team is responsible for development of data analytics & data-empowered platform capabilities across Global E-Commerce. Our mission is to empower our users to leverage and extract actionable insights from data to maximise their potential and efficiency on the global e-commerce platform. In essence, we want to extract facts, attribute causes and predict the future from oceans of data; and our fundamental goals are to reflect business impact, leverage data to support key decisions by lowering decision making complexity and optimising decision making efficacy and efficiency.

Responsibilities
- Participate in business operations of merchants, product growth, major promotional events, and other business scenarios by customizing algorithm strategies to support B-side (merchant-side) operations and ensure continuous growth in merchants' GMV (Gross Merchandise Value).
- Collaborate with product operations and business teams to identify mutually beneficial business models for merchants and the platform in various scenarios (such as live streaming, major promotions, and merchant growth), and implement them through technical solutions.
- Understand e-commerce operations and coordinate with upstream and downstream teams, continuously optimizing data products based on data-driven insights, and developing data strategy products such as data diagnostics and attribution, as well as scenario-specific strategy tools.
- Design and develop various strategies, algorithms, and machine learning techniques to enhance the impact of data assets on business metrics.