Senior Data Scientist - Security & Risk Analytics

Amazon Inc.

Seattle (WA)

On-site

USD 159,000 - 215,000

Full time

4 days ago
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Benefits offered by this job

Health insurance
RSUs
Paid time off
Parental leave

Job summary

Amazon Inc. in Seattle seeks a Senior Data Scientist to tackle large, ambiguous security problems. You will design experiments, develop models, and collaborate with software engineers to move proofs of concept into production while protecting customer trust.

You will mentor teammates, influence leadership, and present findings to senior stakeholders. Strong expertise in SQL, Python, R, and statistical modeling is required, with a proven ability to deliver scalable data solutions in a fast-paced

Qualifications

  • 5+ years of experience with data querying languages or statistical software.
  • 4+ years of data science experience.
  • Experience with statistical models such as multinomial logistic regression.

Responsibilities

  • Define problems and solution approaches autonomously in ambiguous security spaces; analyze large datasets using diverse methods.
  • Deliver scalable models that analyze large datasets efficiently.
  • Build mathematical models to detect and classify data with high accuracy.
  • Prototype models in R or Python; collaborate to production.
  • Lead large projects requiring both business and technical domain expertise.
  • Influence multiple teams and advise on data-driven security decisions.
  • Mentor scientists and participate in code reviews; create technical documentation.

Skills

SQL
Python
Statistical modeling

Tools

AWS QuickSight
Tableau
R Shiny

Job description

Amazon Inc. in Seattle seeks a Senior Data Scientist to tackle large, ambiguous security problems. You will design experiments, develop models, and collaborate with software engineers to move proofs of concept into production while protecting customer trust.

You will mentor teammates, influence leadership, and present findings to senior stakeholders. Strong expertise in SQL, Python, R, and statistical modeling is required, with a proven ability to deliver scalable data solutions in a fast-paced

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