Applied Scientist II, Amazon - Amazon

Description F2 & XCAT Tech Discovery Science is looking for a L5 Applied Scientist to lead our ML visioning, roadmap planning, as well as building Machine Learning solutions to solve economic problems at scale. Discovery uses Machine Learning, Deep Learning, Reinforcement Learning, Causal Inference, and Econometrics/Economics to derive actionable insights about the complex economy of Amazon's retail business. We also develop Statistical Models and Algorithms to drive strategic business decisions and improve operations. We are a science-driven team incubating and building disruptive solutions using cutting-edge technology to solve some of the toughest business problems at Amazon. You will work with business leaders, scientists, and engineers to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable distributed ML models and services. You will partner with scientists, product managers, and engineers to help invent and implement scalable ML, RL, and econometric models while building tools to help our customers gain and apply insights. This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale economic problems, enable measurable actions on the Consumer economy, and work closely with scientists and economists. We are particularly interested in candidates with experience building predictive models and working with distributed systems. As a Sr. Applied Scientist, you bring structure to ambiguous business problems and use science, logic, and practical experience to decompose them into straightforward, scalable solutions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems; you're interested in learning; and you acquire skills and expertise as needed. About the team The mission of our team is to make Amazon's online store the preferred shopping destination for customers by creating discovery and evaluation experiences that delight. We enable customers to discover products they love by using data, computer vision, and machine learning to organize, rank, blend with ads, and create browsable and personalized recommendations. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA | Sunnyvale, CA, USA Basic Qualifications - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience - Experience programming in Java, C++, Python or related language - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing Preferred Qualifications - Experience using Unix/Linux - Experience in professional software development 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 $222,200/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.