Description As a Senior Applied Scientist in Worldwide Defect Elimination (WWDE) - Amazon Stores Customer Service (CS), your role is pivotal in leveraging statistics/machine learning (ML) techniques to address customer issues at scale. This candidate will lead the development of innovative solutions that use causal inference to drive business decisions. The ideal candidate will design and bring their science models to production. As a part of this role, this candidate will collaborate with a team of experts in the field (including internal and academic economists) and move the state of research forward. Key job responsibilities - Research and development of innovative modeling techniques for statistics / ML and causal inference - Establish scientific culture and standards for all scientists (publication, best practices, reviews, etc.) - Deliver solutions to core business problems and influence business partners - Develop scientific talent on the team A day in the life If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan About the team The WWDE team's mission is to understand and resolve all issues impacting customers and connect all organizations in Amazon to customer experiences. Our vision is to be the ultimate steward of the Voice of the Customer (VoC), empowering customer service, and Amazon teams to easily measure, listen, and act on customer feedback. The team broadly supports defect detection, root cause identification, and resolution to earn customer trust. The Customer Service Economics & Optimization team is a force multiplier within this group. Through causal analysis, we estimate the effectiveness of our efforts to delight the customer. Basic Qualifications - PhD, or Master's degree and 6+ years of applied research experience - 3+ years of building machine learning models for business application experience - Experience programming in Java, C++, Python or related language - Experience with machine learning 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. - Expertise in causal inference 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 $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.