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Location
In office (Bengaluru)
Seniority
Middle · 2+ years exp
Employment
Full-Time

First seen by Alion on Nov 4, 2026.

Overview
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Amazon's approach to customer-obsessed science. Get the latest news about innovations in artificial intelligence and machine learning, including job opportunities, publications, conferences, events and more.
Description

Are you passionate about working with Amazon-scale data, advanced analytics, and data science

Do you love bringing data together from diverse systems and sources and working on innovative advanced analytics problems for creating deep understanding of customer behavior and generating actionable business insights Does the idea of working closely with a team of highly experience machine-learning scientists and engineers excite you

We looking for an experienced, self-driven Data Scientist to help us synthesise data into knowledge for our Kindle Direct Publishing business. If you like working with data and want to harness the power of it to develop a deeper understanding of customer behaviour, identify opportunities, impact publishing workflow and influence the business strategy to develop products and features that have a direct impact on the creator and reader experience, this is the role for you!

Key job responsibilities

As Data Scientist, you will connect with world leaders in your field working on similar problems. You will be working with massive-scale data and providing analytic leadership to scientists, product managers, engineers using these data. You will leverage your knowledge in machine learning, advanced analytics, metrics, reporting, and analytic tooling/languages to analyze and translate the data into meaningful insights. You will closely collaborate with business, scientists, and engineers. You will have end-to-end ownership of operational and technical aspects of the insights you are building for the business, and will play an integral role in strategic decision-making. Further, you will build solutions leveraging advanced analytics that enable stakeholders to manage the business and make effective decisions, partner with internal teams to identify process and system improvement opportunities.

About The Team

Minerva is a cross-functional science, analytics, and ML org of highly experienced scientists, BI/data engineers, and software engineers with a critical business mission making revolutionary leaps forward using massive-scale data with advanced analytics and machine learning and helping democratize the publishing industry. We build science-based systems for marketing and content-discovery for indie authors, fraud/abuse, and content risk for our publishing businesses. We also use science to optimize manufacturing, fulfillment, and quality processes.

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
  • 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 in 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
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