Data Scientist, WW Ops, FP&A, WW Ops FP&A

The WW Operations IPAT team is revolutionizing Amazon's financial forecasting through TrendCast, an innovative, automated, science-based top-down forecast modeling that's transforming how we predict Worldwide Operations costs. This innovation approach leverages key performance indicators to generate automated, transparent forecasts with unprecedented frequency. By moving beyond traditional bottom-up planning, TrendCast empowers leadership with real-time insights, enabling swift identification of both risks and opportunities.
As our operational scope rapidly expands into Generative AI, we are also building an intelligent, GenAI-powered Finance Knowledge Base to further reduce the workload on finance teams and facilitate leadership’s decision-making process. We are seeking a driven Data Scientist to help build out these advanced analytical and AI-driven solutions.

Key job responsibilities
In this role, you will be a core contributor to our data science initiatives, working at the intersection of traditional machine learning and Generative AI. You will work closely with senior scientists, engineering, and finance stakeholders to translate complex business problems into scalable models. Your work will directly impact our financial forecasting accuracy (TrendCast) and help develop intuitive, LLM-powered tools that allow finance teams to query, synthesize, and extract insights from our extensive financial knowledge base.

A day in the life
- Develop, train, and evaluate machine learning and statistical models for financial forecasting, ensuring solutions are scalable for large-scale operational challenges.
- Design and implement Generative AI applications, specifically building and optimizing Retrieval-Augmented (RAG) pipelines and LLM-based agents to power our internal Finance Knowledge Base.
- Drive modeling projects from data exploration and feature engineering to model deployment and monitoring, working collaboratively with both technical and non-technical stakeholders.
- Build and maintain robust data pipelines, utilizing distributed computing frameworks to process and analyze petabyte-scale financial and operational datasets.
- Develop a deep understanding of key business metrics and KPIs, connecting model outputs to actionable levers that inform strategic operational decisions.
- Collaborate closely with finance, product, and BIE teams to deploy models, gather feedback, and continuously iterate on both forecasting algorithms and GenAI user experiences.