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Applied Scientist

Job ID: 1784948 | Services LLC


Fashion is extremely fast-moving, visual, subjective, and it presents numerous challenges in areas such as search relevance ranking and optimization, product discovery experience including recommendations and personalization. The vision for Amazon Fashion is to make Amazon the number one online shopping destination for Fashion customers by providing large selections, inspiring and accurate recommendations and customer experience. Are you excited by solving Fashion customer and business problems by applying machine learning and big data technologies? Are you passionate about building systems that process massive amounts of data and make real customer and business impact?

The main focus of Softlines Discovery Science team is to innovate and build engaging search and browse experience for Amazon Fashion customers including organic search relevance ranking, content recommendation and optimization, and understanding of fashion customers shopping intent. The team is looking for an Applied Scientist who is proficient in Machine Learning and can apply the concepts to solve large-scale customer facing problem. We closely collaborate with the core Amazon Search community on building better search algorithms with profound customer impact. 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. Additionally, we are building deep learning models and system to best utilize Amazon customer and product information, such as customer review, product images, etc, for more personalized Softlines shopping experience. We are an interdisciplinary team of Engineers, and Scientists incubating and building day one solutions using cutting-edge technology, to solve large scale problems at Amazon. This role will challenge you to utilize cutting-edge machine learning techniques in the domain of search ranking, deep recommendation system, and computer vision to deliver significant impact for the business.

Major Responsibilities:

· Act as the key contributor in Machine Learning and drive full life-cycle Machine Learning projects.
· Participate in technical efforts within this team and collaboration with other science teams.
· Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production.
· Run A/B experiments, gather data, and perform statistical tests.
· Establish scalable, efficient, automated processes for large-scale data mining, machine-learning model development, model validation and serving.
· Work closely with software engineers and product managers to assist in productionizing your ML models.
· Explore new research initiatives to help shape our long-term science vision.


· PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field
· Experience programming in Java, C++, Python or related language


· Published research work in academic conferences or industry circles.
· Experience with deep learning tools like TensorFlow or PyTorch.
· Experience in building large-scale machine-learning models and infra for recommendation system.
· Effective and crisp verbal and written communication skills with non-technical and technical audiences.
· Experience working with very large real-world data sets and building scalable models from big data.
· Demonstrated successful industrial experience, drives results.
· Thinks strategically and staying on top of tactical execution.
· Exhibits excellent business judgment and understanding of science, engineering, and business trade-offs.