Drimva

Amazon

Data Scientist, OTS - Data ANCHOR Team

$136K–$184K

Austin, TX · Full-time · Posted Oct 26, 2026

Experience
3+ years of data scientist experience and 3+ years of experience with data querying languages, scripting languages, or statistical/mathematical software.
Education
Bachelor’s degree in a quantitative field; a master’s degree in a quantitative field is preferred.

About the job

Develops and deploys data science and AI solutions to improve forecasting, triage, incident prevention, and operational decision-making across Amazon’s global IT operations.

What you'll do

  • Build and deploy forecasting, severity classification, triage, and anomaly detection models for IT operations.
  • Productionize machine learning models through automated pipelines and evaluate their performance and operational impact.
  • Communicate findings and recommendations to stakeholders, and contribute to the team’s ML/AI science roadmap.

What they ask for

  • 3+ years of experience with data querying or scripting languages, or statistical/mathematical software.
  • 3+ years of data scientist experience.
  • Bachelor’s degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science.
  • Experience with statistical models and building and deploying production machine learning models.

Nice to have

  • 2+ years of data visualization experience using AWS QuickSight, Tableau, R Shiny, or similar; experience managing data pipelines.
  • Master’s degree in a quantitative field; experience with AWS technologies and written, verbal, and presentation communication.

Pay

136,000.00 - 184,000.00 USD annually (base salary)

Tools

SQL, Python, R, SAS, Matlab, AWS SageMaker, Step Functions, Lambda

AI focus

Applies machine learning and AI, including Generative AI, to operational forecasting, ticket severity classification and triage, anomaly detection, and agentic AI solutions.

Model-written summary · the original posting is authoritative

First seen Oct 27, 2026 · Last verified Nov 5, 2026 (UTC)