Full-Time

Data Scientist 2

Enterprise Security Products

Amazon

Amazon

10,001+ employees

Global online marketplace and cloud services

Compensation Overview

$136k - $184k/yr

+ Sign-on payments + RSUs

Company Historically Provides H1B Sponsorship

Austin, TX, USA

In Person

Master's, PhD

Category
Data & Analytics (1)
Required Skills
LLM
Python
SAS
R
SQL
Machine Learning
MATLAB
RAG

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Requirements
  • 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
  • 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 STEM
  • Experience applying theoretical models in an applied environment
Responsibilities
  • 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.
  • 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.
  • 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.
  • 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.
  • Prototype rapidly and validate with customers: Turn hypotheses into prototypes in days, not quarters. Iterate based on real customer signal and ship what works.
  • Partner across disciplines: Work directly with SDEs, applied scientists, security researchers, PMs, and UX designers to turn ambiguous problems into shipped solutions. Small team means short lines between you and the decision.
  • Communicate with impact: Translate complex modeling results into clear recommendations for engineers, product leaders, and senior executives. Influence direction with data.
  • Raise the science bar: Contribute to technical and science reviews, mentor teammates, and champion AI-first development practices. Help shape the science culture of a fast-growing team from the ground floor.
Desired Qualifications
  • 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 applying quantitative analysis to solve business problems and making data-driven business decisions
  • Experience in security, anomaly detection, or other low-signal/high-stakes ML domains
  • Experience optimizing AI integrations or building agentic development processes (e.g., Ralph loop, parallelized agentic development)

Amazon operates a global e-commerce platform with a large online marketplace that connects consumers to both direct sales and third-party sellers across many product categories. It earns money from product sales and marketplace fees, Amazon Prime subscriptions, and AWS cloud services, plus a large Amazon Associates affiliate network. The platform combines fast shipping, streaming, cloud computing, and digital services to reach customers across numerous countries. Its goal is to be the world’s most customer-centric company by offering convenient access to a wide range of products and services.

Company Size

10,001+

Company Stage

IPO

Headquarters

Seattle, Washington

Founded

1994

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Simplify Jobs

Simplify's Take

What believers are saying

  • Q2 2026 revenue rose 20% to $201 billion, with AWS up 37%.
  • Andy Jassy says AI demand extends into 2028, supporting sustained cloud bookings.
  • Amazon's market cap topped $3 trillion in August 2026, easing capital access for expansion.

What critics are saying

  • FTC's antitrust trial starts October 2026, targeting Amazon's marketplace pricing and seller practices.
  • New Jersey sued Amazon on August 4, 2026, over DSP driver pay and conditions.
  • Amazon's $220 billion 2026 capex and Texas gas plant expose existential execution and reputational risk.

What makes Amazon unique

  • AWS backlog hit $496 billion in Q2 2026, revealing unmatched enterprise demand visibility.
  • Amazon combines retail, logistics, Prime, ads, and AWS into one cash-generating ecosystem.
  • Trainium chips and reserved 2027 capacity give Amazon custom AI infrastructure leverage.

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Benefits

Flexible Work Hours

Company Equity

Growth & Insights and Company News

Headcount

6 month growth

1%

1 year growth

2%

2 year growth

1%
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