We use cookies. Find out about cookies here. By continuing to browse this site you are agreeing to our use of cookies.

Senior Data Scientist, SDS Science, Seattle, Washington

CategoryData Science
Job typeFull Time
CountryUnited States of America
Job summary
Amazon's Shipping and Delivery Support (SDS) team is a part of Amazon World Wide Customer Service dedicated to support successful package deliveries to Amazon Customers. As a Data Scientist on our team, you'll use Amazon's wealth of data to help answer tough questions like where and when preemptively intervening with a problem is most likely to result in a successful delivery, which signals should alert us that a delivery is at risk of missing its estimate, and what is the relative value of a specific set of support associate actions as they relate to delivery success. You will also leverage Amazon's rich datasets and machine learning techniques to understand customer urgency, and build algorithms to recommend treatment actions to optimize delivery outcome. This role will be a key member of the Shipping and Delivery Support Science Team.

The Senior Data Scientist will work closely with Business Intelligence Engineers, Data Engineers, Product Managers, Software Engineers, and Program Managers to develop statistical and machinelearning models, design and run experiments, and find new ways to improve support experience to optimize the customer experience and Amazon's on-time deliveries. The Scientist will collaborate with technology and product leaders to solve business and technology problems using scientific approaches to build new services that surprise and delight Amazon drivers and our customers. Science at Amazon is a highly experimental activity, although theoretical analysis and innovation are also welcome. Our scientists work closely with software engineers to put algorithms into practice. They also work on cross-disciplinary efforts with other scientists within Amazon.

The key strategic objectives for this role include:
• Understanding drivers, impacts, and key influences on delivery success and support contacts.
• Optimizing support processes to improve the Customer experience and Amazon's on time delivery.
• Automating feedback loops for algorithms in production.
• Collaborate with researchers, software developers, and business leaders to define product requirements and provide analytical support.
• Utilizing Amazon systems and tools to effectively work with terabytes of data.
• Communicating verbally and in writing to business customers and leadership team with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendations

Basic Qualifications:
• Bachelor's degree in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field
• 5+ years professional experience in modeling and statistical analysis of large datasets
• Proven experience in working with databases and SQL in a business environment
• Experience in solving common statistical problems such as classification, regression, and clustering analysis, etc.
• Solid knowledge in experiment design (A/B Testing).
• Ability to work backwards from customer needs, and distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
• Strong analytical and quantitative skills with the ability to use data and metrics to back up assumptions, recommendations and drive actions
• Superior verbal and written communication skills, ability to convey rigorous mathematical concepts and considerations to non-expert audience

Preferred Qualifications:
• Master's degree in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field with at least 4 years of working experience as a Data or Research Scientist
• Compelling communication and influencing skills and participation with demonstrated experience engaging and influencing senior executives
• Proficiency in Python programming is preferred
• Familiarity with AWS SageMaker is a plus
• Experience in implementing machine learning models in production to support real-time inference is a plus

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.