Data Scientist, WW Ops FP&A
Amazon (AI roles) · Bellevue, Washington, USA
No salary listed. Estimated from 344 salary-disclosed Research roles on this board: $225K–$340K (interquartile range; estimate, not the employer's figure).
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The WW Operations IPAT team is revolutionizing Amazon’s financial forecasting through TrendCast, an innovative, automated, science-based top-down forecast modeling engine. As we expand our scope into Generative AI, we are building a sophisticated, LLM-powered Finance Knowledge Base to streamline decision-making. We are seeking a strong Data Scientist II to drive the technical strategy for these advanced analytical and AI-driven solutions. In this role, you will act as a technical lead, translating high-level business ambiguity into scalable, production-grade systems while influencing cross-functional roadmaps.
Key job responsibilities
• Own and solve difficult business problems where the solution approach is unclear, delivering high-quality artifacts that directly influence financial decisions for senior leadership
• Apply a range of data science methodologies (statistical modeling, machine learning, time series analysis, econometrics) to solve complex forecasting challenges
• Design and implement scalable, reliable approaches to extract insights from large, complex datasets across multiple domains
• Develop metrics to quantify the benefits of solutions and measure project progress and success
• Design and implement Retrieval-Augmented Generation (RAG) systems and LLM-based solutions to enhance financial knowledge retrieval and decision support
• Proactively identify and solve challenges related to GenAI solutions including accuracy, latency, and context management
• Partner with finance stakeholders, engineers, and other scientists to identify data requirements and deliver solutions that meet customer needs
• Write clear, factually correct documents with substantial analytical components; explain technical concepts to non-technical audiences
• Provide peer feedback on solutions and results; mentor and teach less experienced data scientists - 2+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- 1+ years of guiding and coaching a group of researchers experience
- 1+ years of working with or evaluating AI systems experience
- 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
- Experience applying theoretical models in an applied environment
Key job responsibilities
• Own and solve difficult business problems where the solution approach is unclear, delivering high-quality artifacts that directly influence financial decisions for senior leadership
• Apply a range of data science methodologies (statistical modeling, machine learning, time series analysis, econometrics) to solve complex forecasting challenges
• Design and implement scalable, reliable approaches to extract insights from large, complex datasets across multiple domains
• Develop metrics to quantify the benefits of solutions and measure project progress and success
• Design and implement Retrieval-Augmented Generation (RAG) systems and LLM-based solutions to enhance financial knowledge retrieval and decision support
• Proactively identify and solve challenges related to GenAI solutions including accuracy, latency, and context management
• Partner with finance stakeholders, engineers, and other scientists to identify data requirements and deliver solutions that meet customer needs
• Write clear, factually correct documents with substantial analytical components; explain technical concepts to non-technical audiences
• Provide peer feedback on solutions and results; mentor and teach less experienced data scientists - 2+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- 1+ years of guiding and coaching a group of researchers experience
- 1+ years of working with or evaluating AI systems experience
- 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
- Experience applying theoretical models in an applied environment
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