Business Research Analyst

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 the Selling Partner Return Reduction space. This will require collaboration with Product, Science and Engineering teams. 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. The Research Analyst will perform Big data analysis to identify patterns, train model to generate product to product relationship and product to brand & model relationship. The Research Analyst is also expected to continuously improve the ML/LLM solutions in terms of precision & recall, efficiency and scalability. The Research Analyst should be able to write clear and detailed functional specifications based on business requirements.

Key job responsibilities
• Collaborate and propose best in class ML/LLM solutions for business requirements
• Dive deep to drive product pilots, demonstrate innovation and customer obsession to steer the product roadmap
• Develop scalable solutions by writing high-quality code, building ML/LLM models using current research breakthroughs and implementing performance optimization techniques
• Coordinate design efforts between Sciences and Software teams to deliver optimized solutions
• Communicate technical concepts to stakeholders at all levels
• Ability to thrive in an ambiguous, uncertain and fast moving ML/LLMuse case developments
• Familiar with ML/LLM models and able to work independently.

About the team
RBS Brand experience (BX) enables WW brands (FBA Sellers and Retail Vendors) with strategic, actionable insights and recommendations to help them grow their business and reduce returns; through recognizing and solving Brands key pain points related to 3 themes: 1) product quality, 2) catalog quality, and 3) selection quality. We do this by: 1) identifying and validating underserved Brand pain points, 2) building proof of concept, solution and capabilities in partnership with Brands, 3) scaling the solution by leveraging tech, 4) launching full scale brand facing solutions to WW brands, and 5) continuously improve solutions through control mechanisms.- Bachelor's degree in Quantitative or STEM disciplines (Science, Technology, Engineering, Mathematics)
- 3+ years of relevant work experience in solving real world business problems using machine learning, deep learning, data mining and statistical algorithms
- Strong hands-on programming skills in Python, SQL. Additional knowledge of Spark, Scala, R, Java desired but not mandatory
- Strong analytical thinking
- Ability to creatively solve business problems, innovating new approaches where required and articulating ideas to a wide range of audiences using strong data, written and verbal communication skills
- Ability to collaborate effectively across multiple teams and stakeholders, including development teams, product management and operations.- Master's degree with specialization in ML, NLP or Computer Vision preferred
- 3+ years relevant work experience in a related field/s (project management, customer advocate, product owner, engineering, business analysis)
- Diverse experience will be favored eg. a mix of experience across different roles - In-depth understanding of machine learning concepts including developing models and tuning the hyper-parameters, as well as deploying models and building ML service - Technical expertise, experience in Data science, ML and Statistics

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