Data Scientist Ii, Enterprise Security Products

Amazon Amazon · Big Tech · Austin, TX · Data Science

Data Scientist II role focused on building AI-first security products, including agentic systems, anomaly detection, and threat classification. The role involves the full ML lifecycle, from problem framing to production deployment and monitoring, with an emphasis on using AI tools to accelerate development. Key responsibilities include powering agentic architectures with models, embeddings, RAG pipelines, and evaluation frameworks, rapid prototyping, and customer validation. The role also involves partnering across disciplines and communicating complex results. The team operates with startup speed at Amazon scale, emphasizing rapid iteration and shipping.

What you'd actually do

  1. Build the intelligence behind AI-first security products: Design, train, and ship ML models that power agentic systems, anomaly detection, threat classification, and automated response — all running across multi-cloud environments.
  2. Own the full science lifecycle: From problem framing and data exploration through model development, evaluation, production deployment, and monitoring. You build it, you ship it, you run it.
  3. Build with AI to build AI: Use agentic coding tools, LLM-powered workflows, and experimental AI tooling to accelerate every phase of your work; from EDA to feature engineering to model iteration. Multiply your velocity and raise the bar for what one scientist can deliver.
  4. Power agentic architectures: Develop the models, embeddings, RAG pipelines, evaluation frameworks, and feedback loops that make multi-agent security systems smart, safe, and customer-ready.
  5. Prototype rapidly and validate with customers: Turn hypotheses into prototypes in days, not quarters. Iterate based on real customer signal and ship what works.

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 working with or evaluating AI systems experience

Nice to have

  • Experience in security products or threat detection
  • Experience with multi-cloud environments
  • Experience with agentic systems and orchestration
  • Experience with RAG pipelines and vector databases
  • Experience with model evaluation frameworks
  • Experience with LLM-powered workflows and agentic coding tools

What the JD emphasized

  • AI-first development practices
  • agentic AI
  • Build with AI to build AI
  • agentic coding tools
  • LLM-powered workflows
  • experimental AI tooling
  • agentic architectures
  • multi-agent security systems
  • Prototype rapidly
  • ship using the latest AI-assisted workflows

Other signals

  • AI-first development practices
  • design and deploy models that detect threats, power intelligent agents, and make security decisions
  • Build with AI to build AI
  • Power agentic architectures
  • Prototype rapidly and validate with customers
  • ship using the latest AI-assisted workflows