Data Scientist, Ww Ops Fp&a

Amazon Amazon · Big Tech · Bellevue, WA · Data Science

Data Scientist II role focused on building LLM-powered financial forecasting and knowledge retrieval systems, including RAG, for Amazon's WW Ops FP&A team. Requires translating business ambiguity into production-grade AI solutions and influencing roadmaps.

What you'd actually do

  1. Own and solve difficult business problems where the solution approach is unclear, delivering high-quality artifacts that directly influence financial decisions for senior leadership
  2. Apply a range of data science methodologies (statistical modeling, machine learning, time series analysis, econometrics) to solve complex forecasting challenges
  3. Design and implement scalable, reliable approaches to extract insights from large, complex datasets across multiple domains
  4. Develop metrics to quantify the benefits of solutions and measure project progress and success
  5. Design and implement Retrieval-Augmented Generation (RAG) systems and LLM-based solutions to enhance financial knowledge retrieval and decision support

Skills

Required

  • 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

Nice to have

  • 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

What the JD emphasized

  • LLM-powered Finance Knowledge Base
  • Retrieval-Augmented Generation (RAG) systems
  • LLM-based solutions
  • GenAI solutions

Other signals

  • LLM-powered Finance Knowledge Base
  • Retrieval-Augmented Generation (RAG) systems
  • LLM-based solutions