Senior Applied Scientist, Retail Pricing Science and Research - Amazon

Description We are seeking experienced Senior Applied Machine Learning Scientists to develop innovative ML solutions in anomaly detection with use cases of price error detection. Amazon retail pricing generates algorithmic prices for 100s of millions of products weekly and ensuring we publish error free and validated price is key to our core retail business. Key job responsibilities - You will partner with engineers, and product leaders to break down complex price error issues, identify key requirements, innovate, design, & deploy appropriate scientific solutions, and successfully drive the creation of positive customer and business impact - You will summarize your research findings, and present via internal papers and science forms - You are adept at translating business objectives into specific quantitative approaches that can be solved with the vast amount of available Amazon data - You are passionate about the getting the science details right, while balancing the practical considerations of real world production models. About the team Retail pricing science is a centralized diverse team of STEM scientists that develop statistical, ML, RL, optimization and economic models that drive pricing for products sold by Amazon worldwide, as well as monitoring of prices and experimentations in pricing. The team has a dual focus on competitiveness and long term financial optimality. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA Basic Qualifications - PhD, or Master's degree and 10+ years of applied research experience - 4+ years of applied research experience - 4+ years of building machine learning models for business application experience - Experience programming in Java, C++, Python or related language - Experience with neural deep learning methods and machine learning Preferred Qualifications - PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field - Experienced with ML techniques in anomaly an error detection. Strong hands on background with deep learning frameworks such as TensorFlow or pytorch. Familiarity with weak supervision and semi-supervised techniques. 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 $136,000/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.