Data Scientist II

Full time

Employment Information

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Are you excited about driving business growth for millions of sellers through application of Machine Learning and other advanced computer science disciplines? Do you thrive in a fast-moving, large-scale environment that values data-driven decision making and sound scientific practices? We are looking for experienced applied scientists to build the next level of intelligence that will help Amazon Marketplace Sellers to succeed and grow their businesses.

Amazon Marketplace enables sellers to put their products in front of hundreds of millions of customers and offers sellers the tools and services needed to make e-commerce successful, efficient and simple. Our team is responsible for building the core intelligence, insights, and algorithms that support a broad range of products and features that Amazon Marketplace Sellers depend on. We are tackling large-scale, challenging problems such as helping sellers to prioritize business tasks, and predicting customer demand for new products, by bringing together petabytes of data from diverse sources across Amazon.

You should have a proven track-record of delivering solutions using advanced computer science approaches. You will be comfortable using a variety of tools and data sources to answer high-impact business questions that impact millions of customers globally, and be able to break down complex information and insights into clear and concise language and be comfortable presenting your findings to audiences with a broad range of backgrounds.

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Key job responsibilities

  • Develop production software systems utilizing advanced algorithms to solve business problems.
  • Analyze and validate data using data, algorithms, and statistical tools to ensure high data quality and reliable insights.
  • Proactively identify interesting areas for deep dive investigations and future product development.
  • Design and execute experiments, and analyze experimental results in collaboration with Product Managers, Business Analysts, Economists, and other specialists.
  • Partner with data engineering teams across multiple business lines to improve data assets, quality, metrics and insights.
  • Leverage industry best practices to establish repeatable applied science practices, principles & processes.

We are open to hiring candidates to work out of one of the following locations:

Seattle, WA, USA


  • 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
  • 2+ years of data scientist experience
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • Experience applying theoretical models in an applied environment


  • Experience in Python, Perl, or another scripting language
  • Experience in a ML or data scientist role with a large technology company

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $111,600/year in our lowest geographic market up to $212,800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit This position will remain posted until filled. Applicants should apply via our internal or external career site.


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