DESCRIPTION

Amazon’s Devices Economic Value team enables measurement and optimization of Amazon Devices long-term value to help Amazon build better products for their customers. Delivering lasting value to customers is in Amazon’s DNA and we are at the core of how the Devices business prioritizes its investments in innovation and optimization on behalf of customers.
Join us to be a part of the team that is at the core of understanding how Amazon Devices drive deeper customer engagement and helps the business make decisions about how to optimize and balance between short term monetization and long term value creation for Amazon Device users. We are seeking a skilled Data Scientist to help us build the future of Devices and Services marketing measurement and its impacts on long term free cash flow for our business.
Key job responsibilities
We are looking for a Data Scientist to drive the development of Devices and Services own Marketing Mix Models, connecting marketing spend and impressions to their effects on long term free cash flow. The Data Scientist will be responsible for partnering to develop the MMM framework that adapts to the unique characteristics of the Devices and Services business model, to drive marketing investment decisions across the Devices business. We expect the Data Scientist to drive marketing measurement innovation, leveraging current advances in machine learning and other modeling frameworks.
About the team
Devices Science team’s mission is to drive measurement and optimization of long term economic value of the Devices business that balances short term and long term tradeoffs across product lifecycle, and drive clear value for Amazon shoppers. We leverage science advancements across causal inference, structural modeling and machine learning, to solve challenging business problems in Amazon Devices. The team spans scientists across a wide range of seniority, tenure and specialization, including economists, data and applied scientists, with dedicated product and engineering partners.

BASIC QUALIFICATIONS

• 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
• Bachelor’s degree
• 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.
  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

Please refer the Job description for details