Senior Manager, Research Science, WW Stores Finance

This role leads the science function in WW Stores Finance as part of the IPAT organization (Insights Planning Analytics and Technology) driving transformative innovations in financial analytics through AI and machine learning across the global Stores finance organization. The successful candidate builds and directs a multidisciplinary team of data scientists applied scientists economists and product managers to deliver scalable solutions that fundamentally change how finance teams generate insights automate workflows and make decisions. As part of the WW Stores Finance leadership team this leader partners with engineering product and finance stakeholders to translate emerging AI capabilities into production systems that deliver measurable improvements in speed accuracy and efficiency. The roles outputs directly inform VP/SVP/CFO/CEO leadership decisions and drive impact across the entire Stores P&L.

Success requires translating complex technical concepts for finance domain experts and business leaders while maintaining deep technical credibility with science and engineering teams. The role demands both strategic visionidentifying high-impact opportunities where AI can transform finance operationsand execution excellence in coordinating project planning resource allocation and delivery across multiple concurrent initiatives. This leader establishes methodologies and models that enable Amazon finance to achieve step-change improvements in both the speed and quality of business insights directly supporting critical processes including month-end reporting quarterly guidance annual planning cycles and financial controllership.



Key job responsibilities
Transformation of Finance Workflows Lead development of agentic AI solutions that automate routine finance tasks and transform how teams communicate business insights. Deploy these solutions across financial analysis narrative generation and dynamic table creation for month-end reporting and planning cycles. Partner with engineering and product teams to integrate these capabilities into production systems that directly support Stores Finance and FGBS automation goals delivering measurable reductions in manual effort and cycle time.

Science-Based Forecasting Develop and deploy machine learning forecasts that integrate into existing planning processes including OP1 OP2 and quarterly guidance cycles. Partner with finance teams across WW Stores to iterate on forecast accuracy applying these models either as alternative viewpoints to complement bottoms-up forecasts or as hands-off replacements for manual forecasting processes. Establish evaluation frameworks that demonstrate forecast performance against business benchmarks and drive adoption across critical planning workflows.

Financial Controllership Scale AI capabilities across controllership workstreams to improve reporting accuracy and automate manual processes. Leverage generative AI to identify financial risk through systematic pattern recognition in transaction data account reconciliations and variance analysis. Develop production systems that enhance decision-making speed and quality in financial close audit preparation and compliance reporting delivering quantifiable improvements in error detection rates and process efficiency.

About the team
IPAT (Insights Planning Analytics and Technology) is a team in the Worldwide Amazon Stores Finance organization composed of leaders across engineering finance product and science. Our mission is to reimagine finance using technology and science to provide fast efficient and accurate insights that drive business decisions and strengthen governance.

We are dedicated to improving financial operations through innovative applications of technology and science. Our work focuses on developing adaptive solutions for diverse financial use cases applying AI to solve complex financial challenges and conducting financial data analysis. Operating globally we strive to develop adaptable solutions for diverse markets. We aim to advance financial science continually improving accuracy efficiency and insight generation in support of Amazons mission to be Earths most customer-centric company.

- Masters degree or equivalent in engineering technology computer science machine learning robotics operations research statistics mathematics or equivalent quantitative field
- Experience leading the architecture and design (architecture design patterns reliability and scaling) of new and current systems or experience with Machine Learning and Large Language Model fundamentals including architecture training/inference lifecycles and optimization of model execution
- Experience managing and deploying ML products
- Demonstrated expertise designing and optimizing model architectures and pipelines

- Experience using complex modeling and analysis to inform key business decisions
- Experience using data and metrics to drive actionable insights at scale
- Experience conveying complex technical concepts to both technical and business audiences
- Knowledge of financial controls and procedures
- Demonstrated success partnering with cross-functional teams and business units
- Experience leading the transformation and automation of traditional methodologies and workflows through AI/Agentic AI

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.

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The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience qualifications and location. Amazon also offers comprehensive benefits including health insurance (medical dental vision prescription Basic Life & AD&D insurance and option for Supplemental life plans EAP Mental Health Support Medical Advice Line Flexible Spending Accounts Adoption and Surrogacy Reimbursement coverage) 401(k) matching paid time off and parental leave. Learn more about our benefits at WA Seattle - 208300.00 - 281800.00 USD annually