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 in quantitative finance, data science, math, advanced analytics, or with strong Python/SQL proficiency and experience with GenAI/LLM tools
This role is central to our 2026 transformation — reshaping how our finance organization thinks, works, and delivers impact, directly influencing executive decisions and new growth initiatives across AWS

This role will be based in Beijing.

Key job responsibilities

• AI-Powered Productivity & Team Upskilling
• Design and deploy AI-driven solutions (leveraging GenAI tools like Amazon Quick Suite) to automate routine reporting — daily revenue flashes, weekly summaries, and MBR/QBR preparation — with a target of 20%+ productivity improvement across the team
• Build natural language interfaces that allow finance team members to query financial data conversationally, democratizing access to insights and reducing dependency on specialized technical skills
• Lead hands-on training and enablement programs to upskill the broader finance team in AI tools, data modeling techniques, and advanced analytics — turning every analyst into a more strategic contributor
• Identify workflow bottlenecks and implement AI-powered process optimizations, particularly in approval chains, deal reviews, and cross-functional coordination
• Develop forecasting and scenario planning models that anticipate market dynamics, competitive pressures, and customer behavior across China and Hong Kong segments
• Build customer concentration risk models and identify strategies to accelerate growth across the mid-tier customer base
• Support competitive intelligence efforts with real-time analytical models on competitor pricing and positioning
• Build models to measure and improve sales productivity, translating marketing pipeline to revenue with greater efficiency

A day in the life
As a Finance Data Manager in AWS Sales Finance, no two days look exactly the same — but every day sits at the intersection of finance, data, and AI.
You'll start mornings analyzing revenue trends across China and Hong Kong segments, refining forecasting models that help leadership anticipate shifts early. Mid-morning, you're collaborating with sales finance analysts to prototype GenAI-powered reporting workflows — automating manual processes like weekly revenue flashes or building natural language interfaces for conversational data querying.

Afternoons may involve joining deal reviews with sales teams, bringing data-driven insights on customer risk and margin analysis to shape multi-million dollar credit structures. You'll also partner with teammates to explore and scale AI tools across the team — not as a formal trainer, but as a hands-on collaborator helping everyone work smarter.

Basic Qualifications

• 4+ years of building financial and operational reports/data sets that inform business decision-making experience
• 4+ years of creating process improvements with automation and analysis experience
• 4+ years of applying key financial performance indicators (KPIs) to analyses experience

Preferred Qualifications

• 4+ years of solving complex business challenges by delivering accurate and timely financial models, analysis, and recommendations that have a proven impact on business (e.g., financial savings, operational improvements, or customer benefits) experience
• MBA, or Six Sigma Black Belt
• Knowledge of SQL/ETL
• Experience working with large-scale data mining and reporting tools (examples: SQL, MS Access, Essbase, Cognos) and other financial systems (examples: Oracle, SAP, Lawson, JD Edwards)
• Experience delivering forecasting, budgeting, and variance analysis, and data interpretation of results
• Knowledge of Python Pandas and time-series forecasting packages

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