Fire TV Data Scientist: ML, Engagement & Ads

Amazon Inc.

Omaha, Northern (NE, KY)

Hybrid

USD 136,000 - 213,000

Full time

6 days ago
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Benefits offered by this job

Health insurance
401(k) matching
Paid time off
Parental leave

Job summary

Amazon.com Services LLC seeks a Data Scientist for the Fire TV Decision Science team. You will design, validate, and operationalize data science solutions to surface customer insights across engagement, retention, ads monetization, and app store performance.

The role emphasizes independent workstreams, cross-team collaboration, and clear communication of complex analyses. Ideal candidates combine strong quantitative foundations with practical ML experience, delivering trusted models and

Qualifications

  • 3+ years of data querying languages (SQL) and scripting (Python) experience.
  • 3+ years of machine learning/statistical modeling and data analysis experience.
  • 2+ years of data scientist experience.
  • Bachelor's degree in a quantitative field.

Responsibilities

  • Design, develop, validate, and maintain ML models and analyses for Fire TV engagement, lifecycle analytics, ads monetization, and Appstore performance.
  • Independently own data science workstreams and partner with senior scientists and stakeholders.
  • Build and refine customer segmentation to enable personalized marketing and engagement.
  • Contribute to A/B experiments, power analyses, guardrails, and success metrics.

Skills

SQL
Python
R
SAS
MATLAB

Education

Bachelor's degree
PhD (preferred)

Tools

A/B testing
Clustering
Time series modeling
Propensity modeling

Job description

Amazon.com Services LLC seeks a Data Scientist for the Fire TV Decision Science team. You will design, validate, and operationalize data science solutions to surface customer insights across engagement, retention, ads monetization, and app store performance.

The role emphasizes independent workstreams, cross-team collaboration, and clear communication of complex analyses. Ideal candidates combine strong quantitative foundations with practical ML experience, delivering trusted models and

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