Business Research Analyst II, RBS Size/Fit
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, the Research Analyst 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 the compatibility program, the Research Analyst performs Big data analysis to identify patterns, train models to generate product-to-product relationships and product-to-brand & model relationships. The Research Analyst also continuously improves the ML solution for higher solution accuracy, efficiency, and scalability. The Research Analyst should write clear and detailed functional specifications based on business requirements as well as write and review business cases.
Key job responsibilities
1. Scoping, driving, and delivering complex projects across multiple teams.
2. Performing root cause analysis by understanding the data needs, pulling the data, and analyzing it to form and validate hypotheses using data.
3. Conducting a thorough analysis of large datasets to identify patterns, trends, and insights that can inform the development of NLP applications.
4. Developing and implementing machine learning models and deep learning architectures to improve NLP systems.
5. Designing and implementing core NLP tasks such as named entity recognition, classification, and part-of-speech tagging.
6. Diving deep to drive product pilots, build and analyze large data sets, and construct problem hypotheses that help steer the product feature roadmap (e.g., using Python, SQL, Spark, TensorFlow, PyTorch).
7. Conducting regular code reviews and implementing quality assurance processes to maintain high standards of code quality and performance optimization.
8. Providing technical guidance and mentorship to junior team members and collaborating with external partners to integrate cutting-edge technologies.
9. Finding scalable solutions for business problems by executing pilots and building deterministic and ML models (plug and play on ready-made ML models and Python skills).
10. Performing supporting research, conducting analysis of larger parts of the projects, and effectively interpreting reports to identify opportunities, optimize processes, and implement changes within their part of the project.
11. Coordinating design efforts between internal and external teams to develop optimal solutions for their part of the project for Amazon’s network. Ability to convince and interact with stakeholders at all levels either to gather data and information or to execute and implement according to the plan.
BASIC QUALIFICATIONS
• Ability to analyze and articulate business issues to a wide range of audiences using strong data, written and verbal communication skills.
• Good mastery of BERT and other NLP frameworks such as GPT-2, XLNet, and Transformer models.
• Experience in NLP techniques such as tokenization, parsing, lexing, named entity recognition, sentiment analysis, and spellchecking.
• Strong problem-solving skills, creativity, and ability to overcome challenges.
• SQL/ETL, Automation Tools.
• Relevant bachelor’s degree or higher.
• 3+ years combined of relevant work experience in a related field (project management, customer advocacy, product ownership, engineering, business analysis) - Diverse experience will be favored, e.g., a mix of experience across different roles.
• Be self-motivated and autonomous with an ability to prioritize well and remain focused when working within a team located across several countries and time zones.
PREFERRED QUALIFICATIONS
• 3+ years combined of relevant work experience in a related field (project management, customer advocacy, product ownership, engineering, business analysis) - Diverse experience will be favored, e.g., a mix of experience across different roles.
• Understanding of machine learning concepts including developing models and tuning hyper-parameters, as well as deploying models and building ML services.
• Experience with computer vision algorithms and libraries such as OpenCV, TensorFlow, Caffe, or PyTorch.
• Technical expertise and experience in Data Science and ML.
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