Amazon operates in a virtual, global eCommerce environment in seven countries across the Globe. Every day, millions of customers rely on Amazon to give them access to one of the world's largest selections of consumer goods. To continue to delight and exceed our customer's expectations, at Amazon, we take the quality of our catalog very seriously. That's where you can help. The RBS group provides catalog augmentation and correction technologies for the Amazon selling community. Our solutions ensure information in Amazon's catalogs is both complete and comprehensive enough to give our customers a great shopping experience every time.
We are looking for a customer obsessed Data Scientist who can apply the latest research, state of the art algorithms and machine learning to build highly scalable systems in the e-commerce domain.
As a successful Data Scientist in Walk the Store, you will work on variations, a concept, which consists of a family of product detail pages that vary by specific product attributes. You will navigate through numerous unexplored areas of product variation, driven by the diversity of millions products and across essential variation components within the amazon eco system, to formulate scaleable mechanisms that deliver superior customer experience. To be successful in this role, you need to be a sophisticated user of advanced data extraction and transformation tools (e.g Python, SQL), and will need to understand the source data and be able to synthesize it down to a form suitable for answering specific business questions, and machine learning. You should be able to model common patterns within the product families using unstructured data, design algorithms to detect anomalies at attribute level which are highly dynamic and differs by product. Work with higher dimensional features, apply scalable decomposition methods and drive feature singularity across the product type. Consider any anomaly in the product attribute is a defect and leverage Self-supervised algorithms to analyze anomalies in product attributes and recommend on possible fixes. You will need to be an expert in sequence modelling, with hands on experience on embedding and localized anomaly detection models. You need to be imaginative with a flair to solve complex problems in a challenging environment with a passion to build solutions that improve the experience of millions of Amazon customers. You will also need to be an expert at communicating insights and recommendations to audiences of varying levels of technical sophistication.
As an experienced research analyst, you will help/mentor other research analyst and develop new algorithms leveraging both classical and deep learning techniques.
Key Responsibilities for this Role:-
• Take ownership of a complex problem statement and define solution strategy to holistically solve that problem for RBS. Scoping, driving and delivering complex projects across multiple teams.
• Big data analysis to identify the defects patterns/process gaps and come up with long term solutions to eliminate the defects/issues.
• Build ecosystem for research analyst and scalable platform for RBS along with cross functional team
• Should be able to communicate effectively with business teams, tech teams as well as scientists from different groups
• Reviews and Makes recommendations that impact development schedules and the success for a product or project.
• Coordinates design effort between internal team and External team to develop optimal solutions for their part of project for Amazon's network.
• Supports identification of down-stream problems (i.e. system incompatibility, resource unavailability) and escalate them to the appropriate level before they become project-threatening.
• Performs supporting research, conduct analysis of the bigger part of the projects and effectively interpret reports to identify opportunities, optimize processes, and implement changes within their part of project.
• Influence all level either to gather data and information or to execute and implement according to the plan.
• Ability to deal with ambiguity and problem solver
• Communicate ideas effectively and with influence (both verbally and in writing), within and outside the team.
Key Performance Areas:
• Ability to understand and solve business problems
• Data analytics and Data Sciences
• Machine learning (Deep Learning)
• Master's degree or higher in Engineering or Business.
• Thorough knowledge of Statistics, Data Sciences and Machine Learning.
• 6+ years of experience in using machine learning to solve business problems and building ML services
• Expert level competency in Python and its packages.
• Master degree / MBA
• Experience on product development
• Expertise in Python and Data Analytics
• Expertise in Text mining
• Expertise in Deep learning models