Applied Scientist Manager, Marketplace Intelligence

Job ID: 10575244 | Amazon.com Services LLC The Sponsored Products and Brands team at Amazon Ads is re‑imagining the advertising landscape through SOTA generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re‑inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. The Marketplace Intelligence (MI) team is looking for an Applied Science Manager to lead a team of scientists and engineers in building production ML and bandit solutions to customise the search experience. We determine which ads to show in Amazon search, where to place them, how many ads to place, and to which customers. This helps shoppers discover new products while helping advertisers put their products in front of the right customers, aligning shoppers’, advertisers’, and Amazon’s interests. To do this, we apply a broad range of machine learning, causal inference, and optimisation techniques to continuously explore, learn, and optimise the allocation and ranking of ads on the search page. We are an interdisciplinary team with a focus on customer obsession and inventing and simplifying. Our primary focus is on improving the SP experience in search by gaining a deep understanding of shopper pain points and developing new innovative solutions to address them. You’ll lead the MI Interleaving team. The Interleaving team’s mission is to personalise and contextualise SP ad allocation on the search page. We do this by modelling shopper responses to the number, placement, and quality of ads. We use online experimentation, simulation, causal modelling, and online feedback to estimate the cost of displacing organic and sponsored content. Then, we incorporate those estimates into ad allocation to deliver an efficient and customised shopping experience for shoppers and improved discoverability and sales for advertisers. You’ll own the experimentation systems, models, and online model serving infrastructure to support these solutions. This is a unique opportunity for someone who wants to have broad business impact, a direct impact on customers and the search experience, build scaled real‑time LLM and ML solutions, and lead a cross‑functional team. If you are interested in machine learning, bandit learning, building production systems, and leading a team to build these solutions, this role is for you. We’re looking for a leader who can help lay out the vision for the team and grow with it. Key job responsibilities Lead a team of scientists and engineers in building scalable machine learning solutions. Develop a vision for contextualising and personalising SP ads in Amazon search. Create, develop, and drive a data‑driven product strategy to define the right quantitative measures of shopper impact, using this to evaluate decisions and opportunities. Tackle and solve challenging science and business problems that balance the interests of advertisers, shoppers, and Amazon. Own a portfolio of pragmatic long‑term investments that drive long‑term growth of the ads and retail businesses. Develop real‑time LLM and ML algorithms to allocate billions of ads per day in advertising auctions. Develop efficient algorithms for multi‑objective optimisation and AI control methods to find operating points for the ad marketplace then evolve them. Develop scientists and ML engineers around machine learning, economics, and optimisation for Advertising. Basic Qualifications 4+ years of applied research experience 3+ years of scientists or machine learning engineers management experience 3+ years of building machine learning models for business application experience PhD, or Master's degree and 6+ years of applied research experience Knowledge of ML, NLP, Information Retrieval and Analytics Experience programming in Java, C++, Python or related language Preferred Qualifications Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers 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 for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign‑on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at USA, VA, Arlington - 183,800.00 - 248,700.00 USD annually USA, WA, SEATTLE - 183,800.00 - 248,700.00 USD annually Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Veterans, military spouses, and people with disabilities are encouraged to apply. #J-18808-Ljbffr Amazon Inc.