Amazon is looking for an analytical Data Scientist to tackle critical data quality challenges with our Amazon Books team. You´ll dive deep into our vast Books Catalog data to uncover root causes of data issues and their downstream impacts, directly influencing how hundreds of millions of customers discover their next great read.

At Amazon Books we believe that reading is essential for a healthy society. As such, we aim to inspire readers by making it easy to read more and get more out of reading. We do this by creating an unmatched book discovery experience for our customers worldwide. We enable customers to discover new books, authors and genres through smart search tools, intelligent interactions and sophisticated recommendations, and we need your help to ensure our data foundation supports these experiences.

If you are looking for an opportunity to solve complex analytical problems in a fast-paced environment working within a smart and passionate team, this might be the role for you. You will conduct sophisticated analyses to identify data quality issues, perform root cause analysis to understand systemic problems, and build prototypes that demonstrate potential solutions. You will work at the intersection of data science, business intelligence, and product development to drive data-driven decisions that improve our catalog quality.

Key job responsibilities

In this role you will:

- Conduct deep-dive analyses of Books Catalog data to identify quality issues, patterns, and anomalies that impact downstream applications and customer experiences

- Perform rigorous root cause analysis using statistical techniques and data mining to understand the underlying drivers of data quality problems

- Build analytical prototypes and proof-of-concepts using ML and agentic technology that demonstrate potential approaches to resolve identified issues

- Collaborate with scientists, engineers, and product teams to communicate findings and influence data quality strategies

- Design and implement scalable data extraction and analysis pipelines to monitor catalog health and track improvements over time

- Translate complex analytical findings into clear, actionable insights for both technical and non-technical stakeholders

- Stay current with data science methodologies and apply best practices to ensure reproducible, high-quality analysis

A day in the life

Day-to-day work varies, but on a typical day you will:

- Run exploratory data analyses to investigate specific data quality concerns or validate hypotheses about catalog issues

- Build visualizations and statistical models to quantify the impact of data problems on customer-facing applications

- Prototype potential solutions using scripting languages and collaborate with engineering teams to assess feasibility

- Present findings to stakeholders including product managers, subject matter experts, and engineering leaders, incorporating their feedback into your analysis

- Participate in team meetings to review metrics, share insights, and contribute to strategic planning for catalog improvements

About the team

The team consists of a collaborative group of scientists, product leaders, and dedicated engineering teams. Our aim is to maintain the world´s most accurate and descriptive set of books metadata, where every title in our catalog is uniquely characterized via a set of high-quality, concise attributes. We believe this is a foundational capacity for any bookstore. We work with sister teams to leverage our systems to drive a diverse array of customer experiences that enable customers to easily identify their ideal next read.

BASIC QUALIFICATIONS

- Experience with machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance

- Experience applying theoretical models in an applied environment

- Experience working as a Data Scientist

- Experience with data scripting languages (e.g., SQL, Python, R, or equivalent) or statistical/mathematical software (e.g., R, SAS, Matlab, or equivalent)

- Experience diving into data to discover hidden patterns and of conducting error/deviation analysis

- Experience effectively communicating complex concepts through written and verbal communication

PREFERRED QUALIFICATIONS

- Currently has, or is in the process of obtaining, a Master´s degree or above in Math, Statistics, Computer Science, or related science field

- Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2

- Experience working in a fast-paced environment similar to a high-tech start-up