Amazon

Data Scientist, North America Stores Expansion

Seattle, WA US
USD 125k - 212k
Python R Matlab Machine Learning Perl AWS SQL
Description
- 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
- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company
- PhD in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science

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.

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 https://amazon.jobs/content/en/how-we-hire/accommodations 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 $125,500/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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
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 an experienced 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
· Lead independent research initiatives in network optimization and financial modeling

The ideal candidate will:
· Drive projects independently and partner with product/engineering teams
· Have strong statistical foundations
· Excel in Python and R programming
· Demonstrate ability to translate complex analyses into business value

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.

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