About Amazon.com:
Amazon.com strives to be Earth's most customer-centric company where people can find and discover virtually anything they want to buy online. By giving customers more of what they want - low prices, vast selection, and convenience - Amazon.com continues to grow and evolve as a world-class e-commerce platform. Amazon's evolution from Web site to e-commerce partner to development platform is driven by the spirit of innovation that is part of the company's DNA. The world's brightest technology minds come to Amazon.com to research and develop technology that improves the lives of shoppers and sellers around the world.

Overview of the role
The Business research Analyst will be responsible for data and Machine learning part of continuous improvement projects across compatibility and basket building space. This will require collaboration with local and global teams, which have process and technical expertise. Therefore, RA should be a self-starter who is passionate about discovering and solving complicated problems, learning complex systems, working with numbers, and organizing and communicating data and reports. In compatibility program, RA perform Big data analysis to identify patterns, train model to generate product to product relationship and product to brand & model relationship. RA also continuously improve the ML solution for higher solution accuracy, efficiency and scalability. RA should writes clear and detailed functional specifications based on business requirements as well as writes and reviews business cases.

Key job responsibilities
• Scoping, driving and delivering complex projects across multiple teams.
• Performs root cause analysis by understand the data need, get data / pull the data and analyze it to form the hypothesis and validate it using data.
• Conducting a thorough analysis of large datasets to identify patterns, trends, and insights that can inform the development of NLP applications.
• Developing and implementing machine learning models and deep learning architectures to improve NLP systems.
• Designing and implementing core NLP tasks such as named entity recognition, classification and part-of-speech tagging.
• Dive deep to drive product pilots, build and analyze large data sets, and construct problem hypotheses that help steer the product feature roadmap (e.g. with use of Python), tools for database (e.g. SQL, spark) and ML platform (tensorflow, pytorch)
• Conducting regular code reviews and implementing quality assurance processes to maintain high standards of code quality and performance optimization.
• Providing technical guidance and mentorship to junior team members and collaborating with external partners to integrate cutting-edge technologies.
• Find the scalable solution for business problem by executing pilots and build Deterministic and ML model (plug and play on readymade ML models and python skills).
• 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.
• Coordinates design effort between internal team and external team to develop optimal solutions for their part of project for Amazon’s network. Ability to convince and interact with stakeholders at all level either to gather data and information or to execute and implement according to the plan.

About the team
Amazon.com operates in a virtual, global eCommerce environment without boundaries, and operates a diverse set of businesses in 14 countries, including Retail, third party marketplaces, eCommerce platforms, web services for developers. Retail Business Service (RBS) organization is a core part of leading customer experience and selling partners experience optimization. This team is part of RBS Customer Experience business unit. The team’s primary role is to create and enhance retail selection on the worldwide Amazon online catalog. The compatibility program handled by this team has a direct impact on customer buying decisions and online user experience. Compatibility program aims to address Customer purchase questions if two products works together, as well as reduce return due to incompatibility.