Amazon
Sr. Applied Scientist, Brand Intellegence and Agentic AI Program
Amazon, Seattle, Washington, United States, 98101
Brand Intelligence And Agentic Ai Program
The Brand Intelligence and Agentic AI program represents the voice of customers with respect to brands: brand recognition, reputation, value, quality, and overall appeal. The team as part of Amazon Retail tech org is hiring an experienced Sr. Applied Scientist to guide the team on science strategies, design ML solutions to solve customer-facing brand shopping challenges at scale, and grow and influence the broader science community. The team uses Machine Learning, Deep Learning, LLM, and Agentic AI to derive actionable insights from understanding customer shopping intent and preferences on brands and develop and experiment with ML solutions to deliver business impact. We also start working with the marketing team to build AI agents to assist them better in their marketing journey with brands insights and knowledge. We are a science-focused team incubating and building disruptive solutions to solve large-scale shopping recommendation and personalization problems to assist our customers easily discover relevant and valuable brands and selection, as well as to help brand owners be successful in reaching promising customers. This is a unique, high visibility opportunity for someone who wants to have direct impact solving customer-facing problems, dive deep into large-scale science problems esp. in the new Agentic AI world, enable measurable actions on the Consumer economy, and work closely with scientists. Key job responsibilities include: Working with Product and Engineering to shape the product vision and provide forward-looking science strategies. Leading scientists in designing and building machine-learning and LLM solutions. Collaborating with partner teams on customer-facing search and browse experiences that will utilize the data and ML models to better serve customers' brand shopping experience. Performing hands-on data analysis, building machine-learning models, running regular A/B tests, and communicating the impact to senior management. Driving continued scientific innovations (Agentic AI, e.g.) as a thought leader and practitioner, and understanding marketing needs on brands understanding. Providing technical and career development guidance to both scientists and engineers in the organization.
The Brand Intelligence and Agentic AI program represents the voice of customers with respect to brands: brand recognition, reputation, value, quality, and overall appeal. The team as part of Amazon Retail tech org is hiring an experienced Sr. Applied Scientist to guide the team on science strategies, design ML solutions to solve customer-facing brand shopping challenges at scale, and grow and influence the broader science community. The team uses Machine Learning, Deep Learning, LLM, and Agentic AI to derive actionable insights from understanding customer shopping intent and preferences on brands and develop and experiment with ML solutions to deliver business impact. We also start working with the marketing team to build AI agents to assist them better in their marketing journey with brands insights and knowledge. We are a science-focused team incubating and building disruptive solutions to solve large-scale shopping recommendation and personalization problems to assist our customers easily discover relevant and valuable brands and selection, as well as to help brand owners be successful in reaching promising customers. This is a unique, high visibility opportunity for someone who wants to have direct impact solving customer-facing problems, dive deep into large-scale science problems esp. in the new Agentic AI world, enable measurable actions on the Consumer economy, and work closely with scientists. Key job responsibilities include: Working with Product and Engineering to shape the product vision and provide forward-looking science strategies. Leading scientists in designing and building machine-learning and LLM solutions. Collaborating with partner teams on customer-facing search and browse experiences that will utilize the data and ML models to better serve customers' brand shopping experience. Performing hands-on data analysis, building machine-learning models, running regular A/B tests, and communicating the impact to senior management. Driving continued scientific innovations (Agentic AI, e.g.) as a thought leader and practitioner, and understanding marketing needs on brands understanding. Providing technical and career development guidance to both scientists and engineers in the organization.