Research Scientist II, Brand Registry
DescriptionThe Brand Registry Science team is looking for a talented scientist to help solve complex problems faced by brands using the latest science solutions. In this role, you will work closely will product team and engineering partners to launch the solution into production and owning the end-to-end solution.We are looking for a highly talented scientist to help build our vision for agent-based intelligent automation. As an applied scientist on the team, you will use large language models' techniques to build automated AI solutions that thinks like human to assist decision making and eventually make autonomous decisions that impacts millions of brands, selling partners, and customers. You will work backwards from data insights and customer feedback to build the right machine learning solutions, collaborate with other domain experts in finding innovative solutions to unsolved problems.An ideal candidate should have extensive experience driving large-scale Machine Learning initiatives, specially in GenAI and LLM applications, from conception to launch in a rapidly evolving environment. Amazon’s growth requires leaders who move fast, have an entrepreneurial spirit to create new solutions, have an unrelenting tenacity to get things done, and are capable of breaking down and solving complex problems.Key job responsibilities
- Understand business challenges by analyzing data and customer feedback
- Collaborate with tech and product teams on building ML strategies, experimentation, implementation and continuous improvement
- Analyze and extract relevant information from large amounts of both structured and unstructured data to design strategies to solve business problems.
- Use large language models and machine learning techniques to create scalable solutions for business problems
- Create business and analytics reports and present to the senior management teams
- Research and implement novel AI solutions and publish research papers
- PhD, or Master's degree and 4+ years of quantitative field research experience
- Experience investigating the feasibility of applying scientific principles and concepts to business problems and products
- Experience analyzing both experimental and observational data sets
- Knowledge of R, MATLAB, Python or similar scripting language
- Experience with agile development
- Experience building web based dashboards using common frameworks
- Demonstrated experience leveraging generative AI tools to enhance workflow efficiency and productivity, with the ability to craft effective prompts and critically evaluate AI-generated outputs in a professional setting
- Experience identifying opportunities to integrate AI solutions into products and services to drive business value