Data Scientist, NA Stores Expansion

Description

Amazon's North America Stores (NAS) connects millions of customers with sellers, offering unparalleled product selection at competitive prices. Our Science team drives this mission through data-driven innovation and research.

We're seeking a Data Scientist to:

· Develop comprehensive data dictionaries and optimize data infrastructure

· Assess financial and operational impacts of new products

· Research and implement state-of-the-art ML, optimization, and AI solutions

· Collaborate with scientists to evaluate algorithms from a business perspective

The ideal candidate will:

· Have strong statistical foundations

· Excel in Python programming and ML Frameworks

. Lead experimentation efforts and drive measurable impact through AB tests across new initiatives.

· Demonstrate ability to translate complex analyses into business value

. Partner with product teams in evaluating the financial and operational impact of new product offerings.

· Partner with science teams across other organizations to develop state of the art algorithms and models.

This role offers the opportunity to shape the future of e-commerce through innovative data science solutions at scale.

Key job responsibilities

As a Data Scientist, you'll leverage advanced analytics to solve complex business problems where solutions aren't immediately clear. Combining business acumen, statistical expertise, and machine learning knowledge, you'll thrive in our collaborative, learning-focused environment.

You'll work with AWS tools including Redshift, SageMaker, Lambda, S3, and EC2, while contributing expertise in areas such as optimization, machine learning, generative-AI, forecasting, and probabilistic/causal ML. Bring your unique specialties to complement our diverse technical ecosystem.

Basic Qualifications

• Bachelor's degree or above in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science

• 1+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience

• 2+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience

• Experience in manipulating/transforming data, model selection, model training, cross-validation and deployment at scale

• Bachelor's degree

Preferred Qualifications

• Master's degree in Operations Research, Statistics, Applied Mathematics, Engineering, Computer Science or related field

• Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)

• Experience with AWS Solutions, including EC2, S3, Redshift, EMR (or Hadoop)

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. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $97,500/year in our lowest geographic market up to $185,000/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.