Description Shopbop is a leading fashion retailor, and part of the Amazon family of companies. The Shopbop Data Scientist partners with business leaders, software teams, and data engineers to create the models and innovations required to advance Shopbop’s business. Whether onboarding industry best-practices for seasonal demand prediction, partnering with engineers to launch ML-enabled features, or experimenting to drive new science approaches, your work will have a significant impact on Shopbop’s mission to be “the destination for style inspiration”. Your work will be a mix of building science-enabled pipelines to solve Shopbop business problems (eg. inventory placement for our expansive product catalog), acting as architect for ML-enabled features, or mentoring our organization of 90 technologists on how to better leverage science. You will have routine exposure to business leaders and opportunities to influence Shopbop’s strategy. As a member of the Technology group you will have access to world-class technologists at Shopbop and our peers at Zappos and Amazon. Shopbop is still early in our adoption of Science and you can influence the tools and methodologies we use to bring science to production. Key job responsibilities - Identify the right models and mechanisms to use to solve ambiguous science problems - Build development plans to launch new science features - Oversee work of peer SDEs on science initiatives - Develop critical path code for critical science features - Align senior leadership and developers on approach A day in the life You start your day reviewing an issue with higher that normal variance on a demand prediction pipeline, you identify there may be a data problem and make a note to raise with the DE team. You then go heads down to work on a new pipeline for Product Categorization, focusing on code you need to demo after standup. Post standup you and a peer TPM lead a discussion on some key tradeoffs and get alignment on next steps. You end the day working with DE, they've found the data bug and will get a fix in. About the team The Shopbop Catalog team supports Shopbop's mission by building software to support our Buying/Planning, Catalog, Studio, Inventory, and Amazon Integration teams. We are a group of 35 technologists across Madison WI, New York NY, and Las Vegas NV. 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 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. 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 $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.