- Seattle, WA
Fashion is extremely fast-moving, visual, subjective, and it presents numerous unique challenges in areas such as search relevance ranking, search defect reduction, product discovery, recommendations and personalization. Are you passionate about building systems that process massive amounts of data? Are you excited by solving Fashion customer and business problems by applying machine learning and big data technologies?
The vision for Softlines Discovery Science team is to create services, processes, tools and platforms to support innovative and engaging search and browse experiences for Amazon Fashion customers. The team is looking for an outstanding Applied Scientist who is proficient in Machine Learning and search relevance algorithms. The team integrates knowledge on causal Inference, and Econometric/Economic Methodologies to derive actionable insights that change the search results towards improving the long term engagement of our customers. We also develop Statistical Models and Algorithms to drive strategic business decisions and improve operations. We are an interdisciplinary team of Engineers, and Scientists incubating and building day one solutions using cutting-edge technology, to solve some of the toughest business problems at Amazon. This role will challenge you to utilize cutting-edge machine learning techniques in the domain of predictive modeling, natural language processing (NLP), and deep learning to deliver significant impact for the business.
• Lead complex projects that design and build machine-learning, natural language processing solutions for our Fashion customers
• Collaborate with partner teams on customer-facing search and browse experiences that will utilize the data and ML models to better serve Amazon Fashion customers' shopping experience.
• Perform hands-on data analysis, build machine-learning models, run regular A/B tests, and communicate the impact to senior management.
• Drive continued scientific innovation as a thought leader and practitioner.
• Provide technical and career development guidance to both scientists and engineers in the organization.
To know more about Amazon science, Please visit https://www.amazon.science
• A Master or PhD in CS machine learning, Statistics, Physics, Applied Math or in a highly quantitative field.
• 3+ years of hands-on experience in predictive modeling and large data analysis.
• Experience with modeling tools such as R, Tensorflow and etc.
• Experience with Spark, Hadoop, Elastic Map Reduce (EMR)
• Experience solving complex business solutions using Machine Learning
• Communication and data presentation skills.
• 3+ years of industry experience in predictive modeling and large data analysis
• Experience building tools that perform large scale data analysis
• Fluent in a modern programming language such as Java, C, C++, or Scala
• Experience with distributed machine learning systems
• A natural curiosity and desire to learn
• Ability to distill problem definitions, models, and constraints from informal business requirements, and to deal with ambiguity and competing objectives
• Published research work in academic conferences or industry circle
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
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