Job Information
Amazon Senior Applied Scientist, MAPLE in Seattle, Washington
Description
Are you excited by the idea of developing algorithms to improve the shopping experience for Amazon customers? Are you looking for new challenges and to solve hard science problems while applying state-of-the-art modeling techniques? Join us and you'll help make the shopping experience better for millions of customers while also advancing the state of Amazon's science through publishing research!
Key job responsibilities
Develop and apply new machine learning algorithms
Use expertise in supervised learning and causal inference to improve ML performance
Scale optimization techniques to drive business value
Design A/B tests and conduct statistical analysis on their results
Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers
Present and publish science research, contributing to Amazon's science community
Mentor junior engineers and scientists.
Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area
About the team
Our team's mission is to surface the right payments-related recommendations to customers at the right time, helping create a rewarding and successful shopping experience for Amazon's customers. Our team's culture is highly collaborative, with an emphasis on supporting each other and learning from one another. We dedicate time each week to focus on personal development and expanding our knowledge as a team. We also highly value having a big impact, both for Amazon's business and for our customers.
Basic Qualifications
3+ years of building machine learning models for business application experience
PhD, or Master's degree and 6+ years of applied research experience
Experience programming in Java, C++, Python or related language
Experience with neural deep learning methods and machine learning
Experience with causal inference modeling
Publication record on machine learning methods
Preferred Qualifications
Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
Experience with large scale distributed systems such as Hadoop, Spark etc.
Experience with reinforcement learning
Experience with optimization packages
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 https://www.amazon.jobs/en/disability/us.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/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 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
-
- Amazon Jobs