About the job
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.
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
Qualifications
Minimum
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
Preferred
Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience working on multi-team, cross-disciplinary projects
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Experience effectively communicating complex concepts through written and verbal communication