Drimva

Amazon

Data Science Manager, Security Compliance Engineering, Stores Security

$175K–$237K

Seattle, WA · Manager · Full-time · Posted Oct 12, 2026

Experience
5+ years building quantitative solutions; 2+ years managing scientists or machine learning engineers; 5+ years applying statistical models at scale and building automated analytical systems.
Education
PhD in computer science, mathematics, statistics, machine learning or equivalent quantitative field.

About the job

Leads a data science and data engineering team measuring and improving embedded security guidance, identifying risk, and building reliable data foundations.

What you'll do

  • Set team strategy, roadmap, and technical direction, aligning work with security and business priorities.
  • Develop metrics, experiments, and analysis to assess guidance accuracy, builder response, and security outcomes.
  • Lead risk identification and feedback systems while building trusted data, reliable pipelines, and a shared team culture.

What they ask for

  • 5+ years of building quantitative solutions as a scientist or science manager experience.
  • 2+ years of scientists or machine learning engineers management experience.
  • 5+ years of applying statistical models for large-scale application and building automated analytical systems experience.
  • PhD in computer science, mathematics, statistics, machine learning or equivalent quantitative field; knowledge of Python or R or other scripting language.

Nice to have

  • Experience in at least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection).
  • Experience with fairness in machine learning and artificial intelligence to detect and remove bias in ML/AI systems.

Pay

175,100.00 - 236,900.00 USD annually (base salary)

Tools

Python, R, NLP, Regression, Classification, Clustering, Anomaly Detection

AI focus

Uses data science and machine learning to identify security risk, determine needed controls, evaluate security guidance, and improve guidance through feedback; preferred experience includes fairness and bias detection in ML/AI systems.

Model-written summary · the original posting is authoritative

First seen Oct 15, 2026 · Last verified Nov 5, 2026 (UTC)