Finance Manager, AWS SMGS Finance, CMHK
Amazon - Beijing, CHN
Posted Apr 23, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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Schedule
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- Weekend work
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Application
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- Assessment
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- Deadline
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Where they hire
State eligibility is not yet verified.
About this role
Finance Manager, AWS SMGS Finance, CMHK Beijing, CHN AWS China is looking for a Finance Data Manager who sits at the intersection of finance, data science, and AI - someone who can fundamentally transform how our Sales Finance team operates. This isn't a traditional finance role or a traditional data science role. It's a force multiplier position designed to scale team productivity, embed AI into everyday workflows, and elevate our entire organization from reactive reporting to proactive, insight-driven business partnership. You will be the catalyst that helps our team move from reporting the news to making the news - building the models, tools, and capabilities that turn our finance organization into a technology-enabled strategic advisory function. Join AWS Sales Finance as a Finance Data Manager at the intersection of finance, data science, and AI - a force multiplier role designed to transform how our team operates by embedding GenAI into everyday workflows and driving productivity gains across the organization. Design and deploy AI-driven solutions to automate routine reporting (daily revenue flashes, MBRs, QBRs) and build natural language interfaces for conversational data querying Champion finance AI enablement by partnering with the team to explore, adopt, and scale AI tools and advanced analytics capabilities - helping elevate how the entire team works Develop forecasting and scenario planning models across China and Hong Kong segments, including customer concentration risk models and competitive intelligence analytics Build models to measure and improve sales productivity, translating marketing pipeline to revenue with greater efficiency Requires 5+ years
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