Our brand understanding and intelligence program represents the voice of customers with respect to brands: brand recognizability, reputation, value, quality, and overall appeal. The team as part of Amazon Retail org is hiring an experienced science leader to guide the team on science strategies, design ML solutions (including the new Agentic AI agents) 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 (well recognized brands, premium brands, new and trending brands, relevant top brands matching customer searches, or individual customer-level brand preference), and develop and experiment with ML solutions to deliver business impact. 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 being successful to reach 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 economic problems, enable measurable actions on the Consumer economy, and work closely with scientists.
Key job responsibilities
- Lead team science vision and strategies and influence business and product on the overall product vision.
- Lead scientists design and build machine-learning and LLM solutions.
- Collaborate with partner teams on customer-facing search and browse experiences that will utilize the data and ML models to better serve customers' shopping experience.
- Perform hands-on data analysis, build machine-learning models, run regular A/B tests, and communicate the impact to senior management.
- Drive continued scientific innovation as a thought leader and practitioner.
- Provide technical and career development guidance to both scientists and engineers in the organization.
