Skip to main content

Data Scientist, FBA Inventory

Job ID: 1787805 | Services LLC


Job summary
FBA Inventory team is looking for a passionate and creative Data Scientist to join our cross-domain science team of data scientists, applied scientists, research scientists, and economists. As a data scientist you will be responsible for generating data-driven insights influencing business directions and product/policy designs, building ML models to learn Seller and customer behaviors, and collaborating with business and software teams to solve key challenges facing the worldwide FBA Seller business, including 1) improving FBA Seller inventory efficiency, 2) efficiently balancing the supply and demand of FBA Seller capacity, 3) closing worldwide selection gap by enabling global selling profitability, and 4) driving out costs across the FBA supply chain to spin the flywheel.

Key job responsibilities
As a member of the science team, you will play an integral part in Amazon's FBA inventory management with the following technical and leadership responsibilities:
· Solve real-world problems by analyzing large amounts of business data, diving deep to identify business insights and opportunities, designing simulations and experiments, developing statistical and ML models by tailoring to business needs, and collaborating with Scientists, Engineers, BIE's, and Product Managers.
· Write code (Python, Scala, etc.) to analyze data and build innovative statistical and machine learning models to drive FBA growth and efficiency.
· Translate business problems into specific analytical questions and form hypotheses that can be answered with available data using scientific methods or identify additional data needed in the master datasets to fill any gaps
· Retrieve, analyze, synthesize, and present historical data in a format that is immediately useful to answer specific questions, improve system performance, or support decision making.
· Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication.
· Proactively seek to identify business opportunities and insights and provide solutions to shape key business processes and policies based on a broad and deep knowledge of Amazon data, industry best-practices, and work done by other teams.

A day in the life
In this role, you will be a technical expert with significant scope and impact. You will work with Product Managers, Software Engineers, and other Scientists, to deeply understand FBA Seller business problems and priorities. You will form hypotheses, analyze Seller and customer data using statistical methods, build new and enhance existing ML models, generate insights and recommendations to address a range of problems on Seller inventory management in order to optimize Seller experience and facilitate their growth. The successful Data Scientist will have strong bias for action needed in a startup environment, with leadership skills, proven ability to build and manage medium-scale modeling projects, identify data requirements, build methodology and tools that are statistically grounded. It will be a person who enjoys diving deep into data, doing analysis, discovering root causes, and designing long-term scientific solutions. We are seeking someone who can thrive in a fast-paced, high-energy and fun work environment where we deliver value incrementally and frequently. We value highly technical people who know their subject matter deeply and are willing to learn new areas. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career.

About the team
Sellers are a critical part of Amazon’s ecosystem to deliver on our vision of offering the Earth’s largest selection and lowest prices. Fulfillment By Amazon (FBA) enables Sellers to provide fast and efficient deliver to their customers using Amazon fulfillment services. In 2020, Sellers enjoyed strong growth using FBA shipping more than half of all products offered on Amazon. To our consumers, FBA provides a broad and diverse inventory of products from Books, Electronics and Apparel to Consumables and beyond with many of them available with 1-Day shipping. The FBA Inventory team within the Amazon Supply Chain Optimization Technology (SCOT) organization is the core team in charge of fulfillment services to our Sellers.


· Master’s degree (or Bachelors degree or 5+ years of experience) in a quantitative discipline such as Statistics, Mathematics, Data Science, Business Analytics, Economics, Finance, Engineering, or Computer Science
· 2+ years of experience working as a data scientist or a similar role involving data extraction, analysis, statistical modeling, and communication
· 2+ years of experience using data querying languages (e.g. SQL, Hadoop/Hive)
· Strong Analytical skills – has ability to scope out business problems to be solved, start from ambiguous problem statements, identify and access relevant data, make appropriate assumptions, perform insightful analysis and draw conclusion relevant to the business problem.
· Strong background and experience using Python and data manipulation/analysis libraries such as Scikit-learn and Pandas for analyzing and modeling data.
· Expert-level knowledge of SQL in a business environment
· Excellent communication skills. Proven ability to communicate verbally and in writing to technical peers and business teams, educating them about our systems, as well as sharing insights and data-driven recommendations


· 4+ years’ experience in a ML or Data Scientist role with a large technology company.
· Extensive knowledge and practical experience in several of the following areas: machine learning, statistics, data analytics, NLP, deep learning, recommendation systems, information retrieval.
· Experience with AWS technologies like Redshift, SageMaker, EC2, Lambda, & EMR
· Experienced in managing large and disparate data sources

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