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Sr. Applied Scientist

Amazon

$150,400 - $260,000
Nov 10, 2025
Sunnyvale, CA, United States of America
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Amazon Advertising is looking to increase traffic monetization and merchandise sales without compromising the shopper experience by developing and deploying advanced machine learning models.

Requirements

  • 5+ years of building machine learning models for business application experience
  • Experience programming in Java, C++, Python or related language
  • Experience with neural deep learning methods and machine learning
  • Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
  • Experience with large scale distributed systems such as Hadoop, Spark etc.

Responsibilities

  • Be a strong contributor to Machine Learning; lending effort within this team and across other teams.
  • Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience.
  • Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.
  • Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.
  • Run A/B experiments, gather data, and perform statistical analysis.
  • Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
  • Research new and innovative machine learning approaches.

Other

  • work safely and cooperatively with other employees, supervisors, and staff
  • adhere to standards of excellence despite stressful conditions
  • communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service
  • follow all federal, state, and local laws and Company policies.
  • exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation.