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Description

The Region Flexibility Engineering (RFE) team builds and leverages foundational infrastructure capabilities, tools, and datasets needed to support the rapid global expansion of Amazon's SOA infrastructure. Our team focuses on robust and scalable architecture patterns and engineering best practices, driving adoption of ever-evolving and AWS technologies. RFE is looking for a passionate, results-oriented, inventive Data Scientist to refine and execute experiments towards our grand vision, influence and implement technical solutions for regional placement automation, cross-region libraries, and tooling useful for teams across Amazon.

As a Data Scientist in Region Flexibility, you will work to enable Amazon businesses to leverage new AWS regions and improve the efficiency and scale of our business. Our project spans across all of Amazon Stores, Digital and Others (SDO) Businesses and we work closely with AWS teams to advise them on SDO requirements. As innovators who embrace new technology, you will be empowered to choose the right highly scalable and available technology to solve complex problems and will directly influence product design. The end-state architecture will enable services to break region coupling while retaining the ability to keep critical business functions within a region. This architecture will improve customer latency through local affinity to compute resources and reduce the blast radius in case of region failures. We leverage off the sciences of data, information processing, machine learning, and generative AI to improve user experience, automation, service resilience, and operational efficiency.

Key job responsibilities

As an RFE Data Scientist, you will work closely with product and technical leaders throughout Amazon and will be responsible for influencing technical decisions and building data-driven automation capabilities in areas of development/modeling that you identify as critical future region flexibility offerings. You will identify both enablers and blockers of adoption for region flex, and build models to raise the bar in terms of understanding questions related to data set and service relationships and predict the impact of region changes and provide offerings to mitigate that impact.

About the team

The Regional Flexibility Engineering (RFE) organization supports the rapid global expansion of Amazon's infrastructure. Our projects support Amazon businesses like Stores, Alexa, Kindle, and Prime Video. We drive adoption of ever-evolving and AWS and non-AWS technologies, and work closely with AWS teams to improve AWS public offerings. Our organization focuses on robust and scalable solutions, simple to use, and delivered with engineering best practices. We leverage and build foundational infrastructure capabilities, tools, and datasets that enable Amazon teams to delight our customers. With millions of people using Amazon’s products every day, we appreciate the importance of making our solutions “just work”.

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

- Experience applying theoretical models in an applied environment

Preferred Qualifications

- Experience in Python, Perl, or another scripting language

- Experience in a ML or data scientist role with a large technology company

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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.