Amazon.com, Inc.-posted about 1 month ago
Full-time • Mid Level
Seattle, WA
5,001-10,000 employees
General Merchandise Retailers

The AWS Compliance & Security Assurance Engineering team builds tools and services that scale AWS's ability to exceed security and compliance expectations for our regulators, auditors, and customers globally. We create efficiencies for our teams while maintaining transparency for our customers. As a Data Scientist on our data team, you'll have a unique opportunity to build solutions that scale security assurance capabilities through AI-driven approaches. You'll leverage advanced analytics, machine learning techniques, and state-of-the-art AI technologies on top of highly complex datasets to transform our security assurance operations. You'll also help shape our data science roadmap, fostering data-driven decision-making and delivering significant business impact through innovative methodologies. The ideal candidate brings a strong background in automation by leveraging GenAI Large Language Models (LLMs), combined with experience analyzing complex datasets and a proven ability to transform business needs into deliverables. If you're passionate about applying AI to security challenges in a dynamic environment that offers startup-like autonomy with enterprise impact, we want to hear from you.

  • Analyze and extract hidden insights from complex, large-scale datasets using advanced statistical and AI techniques, using hands-on expertise in data wrangling and manipulation.
  • Identify high-impact business improvement opportunities, lead the design and execution of data science initiatives to address them.
  • Apply statistical and ML knowledge to specific business problems and data.
  • Leverage Vision Language Models (VLMs) and Large Language Models (LLMs) to analyze document/image structure, perform content understanding and metadata extraction.
  • Rapidly prototype and test AI solutions, while iterating quickly based on data and feedback.
  • Collaborate cross-functionally to deeply understand business requirements, customer needs, and technical constraints; transforming discovered information into data-driven solutions and actionable recommendations.
  • Communicate complex technical concepts to technical and non-technical stakeholders; present compelling insights and evidence-based recommendations to leadership.
  • Stay up-to-date on the latest advancements in AI and identify opportunities to apply emerging techniques to the space.
  • Collaborate with Business Intelligence, Data Engineers and SDEs to drive the collection of new data and refinement of existing data sources to continually improve data quality.
  • Actively participate in team design reviews, data modeling discussions, brainstorming activities while mentoring colleagues in state-of-the-art AI tools and methodologies.
  • 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
  • Experience applying theoretical models in an applied environment
  • Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field, or Bachelor's degree and 5+ years of data scientist experience
  • Experience with AWS technologies
  • Experience with one of the following areas: machine learning technologies, Reinforcement Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP) or related applications
  • Experience in a ML or data scientist role with a large technology company
  • Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
  • Experience communicating technical concepts and processes using clear, simple language and visuals
  • Experience with Large Language Models (LLMs) and Vision Language Models (VLMs).
  • Experience in text data manipulation.
  • equity
  • sign-on payments
  • medical
  • financial
  • other benefits
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