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Description

Marca represents the voice of the customer with respect to brands: their recognizability, reputation, value, quality, and overall appeal. The Marca team (as part of NA Store UPMT org) is hiring an experienced science leader to guide the team on science strategies, design ML solutions to solve customer-facing problems at scale, and grow and influence the broader science community. The team uses Machine Learning, Deep Learning, Reinforcement Learning, and Causal Inference 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 quality 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.

Basic Qualifications

PhD in computer science, ML or related fields. 6+ years experience in Data Science and Machine Learning in industry and/or academia. Track record of thought leadership and contributions that have advanced the field. Strong skills in collaboration and teamwork Strong record of delivery in industry and academic contexts using Machine Learning. Ability to handle multiple competing priorities in a fast-paced environment. Excellent written and verbal communication skills. Ability to handle multiple competing priorities in a fast-paced environment.

Preferred Qualifications

- PhD in Machine Learning, Computer Science, Statistics, or related field

- Expertise building large-scale machine-learning models

- Experience on building recommendation systems, personalization and customer understanding solutions

- Expertise with Big Data technologies such as AWS, Hadoop, Spark, and LLM knowledge.

- Proven records of building complex software systems that have been successfully delivered to customers

- Expertise with machine learning, data mining, and/or statistical analysis tools

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $179,000/year in our lowest geographic market up to $309,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.