Applied Science Manager, Private Brands Discovery

The Private Brands Discovery team designs innovative machine learning solutions to enhance customer awareness of Amazon’s own brands and help customers find products they love. This interdisciplinary team of scientists and engineers incubates and develops disruptive solutions using cutting-edge technology to tackle some of the most challenging scientific problems at Amazon. To achieve this, the team utilizes methods from Natural Language Processing, deep learning, large language models (LLMs), multi-armed bandits, reinforcement learning, Bayesian optimization, causal and statistical inference, and econometrics to drive discovery throughout the customer journey. Our solutions are crucial to the success of Amazon’s private brands and serve as a model for discovery solutions across the company.

This role presents a high-visibility opportunity for someone eager to make a business impact, delve into large-scale problems, drive measurable actions, and collaborate closely with scientists and engineers. As a team lead, you will be responsible for developing and coaching talent, guiding the team in designing and developing cutting-edge models, and working with business, marketing, and software teams to address key challenges. These challenges include building and improving models for sourcing, relevance, and CTR/CVR estimation, deploying reinforcement learning methods in production etc.

In this role, you will be a technical leader in applied science research with substantial scope, impact, and visibility. A successful team lead will be an analytical problem solver who enjoys exploring data, leading problem-solving efforts, guiding the development of new frameworks, and engaging in investigations and algorithm development. You should be capable of effectively interfacing between technical teams and business stakeholders, pushing the boundaries of what is scientifically possible, and maintaining a sharp focus on measurable customer and business impact. Additionally, you will mentor and guide scientists to enhance the team's talent and expand the impact of your work.
- 3+ years of scientists or machine learning engineers management experience
- Knowledge of ML, NLP, Information Retrieval and Analytics
- Expert in developing large-scale ML systems in a production environment
- Extensive experience applying theoretical models in an applied environment
- Demonstrated proficiency in deep learning models, experience building production level causal inference models
- Expert in more than one more major programming / scripting languages (Python, Scala, PySpark or similar)
- Excellent written and verbal communication skills while addressing both technical and business people; ability to speak at a level appropriate for the audience.
- Experience coaching and reviewing work of junior ML Scientists, making great hiring decisions.- Experience building machine learning models or developing algorithms for business application
- Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
- Experience building machine learning models or developing algorithms for business application
- Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
- Team building and science recruiting experience
- Comprehension of tech stacks and could stay on top of tactical execution
- Strong doc writing skills
- Strong fundamentals in problem solving, algorithm design and complexity analysis
- Proven track record of delivering ML models in production
- External Publications

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 $165,500/year in our lowest geographic market up to $286,000/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.