Senior Data Scientist, Personalization & Discovery

Amazon

Seattle (WA)

On-site

USD 159,000 - 215,000

Full time

8 days ago
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Benefits offered by this job

Health insurance
RSUs
Paid time off
Parental leave

Job summary

Amazon Prime Video is seeking a data scientist to help build data-driven frameworks for personalization and content discovery. You will work on fast-paced, cross-functional projects that influence what millions of customers see.

The role requires strong problem-solving, stakeholder communication, and the ability to balance rigor with delivery speed. You will design end-to-end data science workflows, develop scalable analyses, and mentor peers on a data science team while staying current with

Qualifications

  • 5+ years of data querying languages (e.g. SQL) or scripting languages (e.g. Python) experience.
  • 4+ years of data scientist experience.
  • Bachelor's degree.
  • Experience with statistical models e.g. multinomial logistic regression.

Responsibilities

  • Use advanced statistical and machine learning techniques to extract insights from large data sets.
  • Design and implement end-to-end data science workflows from data acquisition to deployment.
  • Support scalable data analyses by building datasets for analytics and ML use cases.
  • Partner with product stakeholders to identify data-driven opportunities to improve customer experience.
  • Communicate findings to technical and non-technical stakeholders.
  • Stay up-to-date on data science tools and best practices and evangelize them across the org.

Skills

SQL
Python
R
SAS
MATLAB

Education

Bachelor's degree

Tools

SQL
Python
R
SAS
MATLAB

Job description

Amazon Prime Video is seeking a data scientist to help build data-driven frameworks for personalization and content discovery. You will work on fast-paced, cross-functional projects that influence what millions of customers see.

The role requires strong problem-solving, stakeholder communication, and the ability to balance rigor with delivery speed. You will design end-to-end data science workflows, develop scalable analyses, and mentor peers on a data science team while staying current with

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