Advise CIOs, CTOs, CDAOs and CFOs on AI as a technology problem. Tie what the business wants back to the platform, talent and governance decisions that have to come first.
Design the operating model. Where AI capability lives, who runs it, how it's funded, how it moves through the delivery lifecycle, and how it's governed once it's in production.
Set the platform and cloud readiness strategy that makes enterprise AI possible. You won't build it. You'll decide what good looks like and hold the line on it.
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Support the team in driving end-to-end growth initiatives across assortment, traffic, conversion, and seller performance through data analysis and structured problem solving.
Assist in strategic projects and growth experiments, including promotional mechanics, subsidy programs, flash sales, and other platform initiatives to improve business performance.
Analyze user behavior, marketplace trends, competitor activities, and business performance to identify growth opportunities and generate actionable insights.
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Support the team in driving end-to-end growth initiatives across assortment, traffic, conversion, and seller performance through data analysis and structured problem solving.
Assist in strategic projects and growth experiments, including promotional mechanics, subsidy programs, flash sales, and other platform initiatives to improve business performance.
Analyze user behavior, marketplace trends, competitor activities, and business performance to identify growth opportunities and generate actionable insights.
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Participate in defining and continuously improving data quality standards, judgment rules, and acceptance criteria for large model training and evaluation scenarios.
Review data outputs against quality standards, identify issues, drive correction loops, and ensure accuracy and consistency.
Assess complex, ambiguous, and boundary cases, and turn decisions into reusable judgment rules and knowledge assets.
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Participate in defining and continuously improving data quality standards, judgment rules, and acceptance criteria for large model training and evaluation scenarios.
Review data outputs against quality standards, identify issues, drive correction loops, and ensure accuracy and consistency.
Assess complex, ambiguous, and boundary cases, and turn decisions into reusable judgment rules and knowledge assets.
...
Participate in defining and continuously improving data quality standards, judgment rules, and acceptance criteria for large model training and evaluation scenarios.
Review data outputs against quality standards, identify issues, drive correction loops, and ensure accuracy and consistency.
Assess complex, ambiguous, and boundary cases, and turn decisions into reusable judgment rules and knowledge assets.
...