Amazon
Data Scientist II, PXT Central Science
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We are seeking an exceptional Data Scientist to join our team in PXT Central Science. The ideal candidate will thrive in a dynamic, multifaceted role where you'll translate complex business challenges into rigorous quantitative frameworks, extract actionable insights from structured and unstructured datasets, and architect science-backed, scalable solutions that elevate the experience of our 1 million+ employees worldwide. If you're energized by the opportunity to apply data science to our mission of making Amazon Earth's Best Employer, we want to hear from you.
Key Responsibilities
Own the design, development, and maintenance of scalable models and prototypes leveraging statistical, machine learning, or GenAI methodologies to enhance employee experience.
Partner with scientists, engineers, and product leaders to solve for employee experience defects using scientific approaches, building new services and tools that deliver measurable impact.
Author and maintain detailed technical documentation related to the projects you drive.
Communicate results to diverse audiences of varying technical background with effective writing, visualizations, and presentations.
Stay current with emerging methods and technologies, and implement them strategically to amplify the team’s impact.
Basic Qualifications
2+ years of data scientist experience.
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience.
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience.
1+ years of guiding and coaching a group of researchers experience.
1+ years of working with or evaluating AI systems experience.
1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience.
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM).
Experience applying theoretical models in an applied environment.
Preferred Qualifications
Ph.D. in Science, Technology, Engineering, or Mathematics (STEM).
Knowledge of machine learning concepts and their application to reasoning and problem-solving.
Experience in Python, Perl, or another scripting language.
Experience in a ML or data scientist role with a large technology company.
Experience defining and creating benchmarks for assessing GenAI model performance.
Experience working on multi-team, cross-disciplinary projects.
Experience applying quantitative analysis to solve business problems and making data-driven business decisions.
Experience effectively communicating complex concepts through written and verbal communication.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers.
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We are seeking an exceptional Data Scientist to join our team in PXT Central Science. The ideal candidate will thrive in a dynamic, multifaceted role where you'll translate complex business challenges into rigorous quantitative frameworks, extract actionable insights from structured and unstructured datasets, and architect science-backed, scalable solutions that elevate the experience of our 1 million+ employees worldwide. If you're energized by the opportunity to apply data science to our mission of making Amazon Earth's Best Employer, we want to hear from you.
Key Responsibilities
Own the design, development, and maintenance of scalable models and prototypes leveraging statistical, machine learning, or GenAI methodologies to enhance employee experience.
Partner with scientists, engineers, and product leaders to solve for employee experience defects using scientific approaches, building new services and tools that deliver measurable impact.
Author and maintain detailed technical documentation related to the projects you drive.
Communicate results to diverse audiences of varying technical background with effective writing, visualizations, and presentations.
Stay current with emerging methods and technologies, and implement them strategically to amplify the team’s impact.
Basic Qualifications
2+ years of data scientist experience.
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience.
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience.
1+ years of guiding and coaching a group of researchers experience.
1+ years of working with or evaluating AI systems experience.
1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience.
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM).
Experience applying theoretical models in an applied environment.
Preferred Qualifications
Ph.D. in Science, Technology, Engineering, or Mathematics (STEM).
Knowledge of machine learning concepts and their application to reasoning and problem-solving.
Experience in Python, Perl, or another scripting language.
Experience in a ML or data scientist role with a large technology company.
Experience defining and creating benchmarks for assessing GenAI model performance.
Experience working on multi-team, cross-disciplinary projects.
Experience applying quantitative analysis to solve business problems and making data-driven business decisions.
Experience effectively communicating complex concepts through written and verbal communication.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers.
#J-18808-Ljbffr