Job description

Love using AI to solve big, messy problems that actually move a business? Come lead the science team that figures out where every advertiser is on their growth journey, and what to do next to help them achieve their goals. Advertising is one of the fastest growing parts of our business, and science sits at the heart of how we help brands succeed. We're looking for an experienced science leader to build, grow, and guide a team of applied scientists working on one of our most exciting challenges: figuring out, for each brand, the smartest next step they can take to grow, and turning that into a clear, personalized recommendation the people who work with those brands can act on right away. If you want real ownership, a team to grow, and problems that matter to millions of businesses, we'd love to talk. Key job responsibilities You'll lead and grow a team of applied scientists and software engineers working on an AI-first mission to understand where every advertiser is in their growth journey and turning that into clear, personalized guidance the people who work with those brands can act on. A big part of our work is understanding where each advertiser is in their growth journey using that to decide the right level of support each one requires to meet their goals. Day to day that means: Set the long-term scientific vision for modeling each advertiser's growth journey, pinpointing their best next opportunities, and shaping the multi-year roadmap to get there Guide the science that pulls many signals, a brand's health, retail, and advertising performance, into one unified, personalized set of recommendations for teams to act on. Hire, coach, and develop scientists and engineers, and build a team known for a high scientific bar. Partner with product and engineering to take models from early research into production, and make sure the guidance genuinely helps brands grow. Set quality standards, catch at-risk work early, and make the hard trade-off calls. A day in the life No two days look the same. You might start by reviewing a new modeling approach with your scientists, then meet with product and engineering partners to agree on what to build next. You'll dig into results, ask hard questions about whether a model is really moving the business, and coach a manager through a tricky call. Your customers are the teams who work directly with brands, and the brands themselves, who lean on your team's recommendations to decide where to invest and how to grow. About the team Sales AI is a central science and engineering organization within Amazon Advertising Sales. Our mission is to power selling motions and account team workflows with state-of-the-art AI and ML services. We're investing in a range of sales intelligence models, including advertiser insights, recommendations, and generative AI-powered applications woven throughout account team workflows. We care about a high scientific bar, real business impact, and taking ideas all the way into production. Most of all, we like working with curious people who want to drive real, lasting impact for our customers. - 10+ years of practical work applying ML to solve complex problems for large-scale applications experience - Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives - Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track - Experience setting science research direction and strategy across multiple teams and organizations - PhD or Master's in Computer Science, Machine Learning, or a related field, or equivalent applied research experience - 5+ years of people management experience, with a proven track record of leading and scaling data science or engineering teams. - Experience leading teams focused on recommender systems, personalization, or behavioral modeling. - Experience designing Hidden Markov Models (HMMs), latent-state frameworks, or deep sequential models. - Strong background in A/B testing, quasi-experimental designs, or causal modeling to measure incremental impact. - Proven track record of deploying generative AI in production environments to personalize, explain, or enhance user recommendations. 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 amazon.jobs 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 amazon.jobs . USA, WA, SEATTLE - 218,800.00 - 295,900.00 USD annually

Requirements

Must-haves

Key job responsibilities
Set the long-term scientific vision for modeling each advertiser's growth journey, pinpointing their best next opportunities, and shaping the multi-year roadmap to get there
Guide the science that pulls many signals, a brand's health, retail, and advertising performance, into one unified, personalized set of recommendations for teams to act on.
Hire, coach, and develop scientists and engineers, and build a team known for a high scientific bar.
Partner with product and engineering to take models from early research into production, and make sure the guidance genuinely helps brands grow.
Set quality standards, catch at-risk work early, and make the hard trade-off calls.
A day in the life
About the team
10+ years of practical work applying ML to solve complex problems for large-scale applications experience
Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track
Experience setting science research direction and strategy across multiple teams and organizations
PhD or Master's in Computer Science, Machine Learning, or a related field, or equivalent applied research experience
5+ years of people management experience, with a proven track record of leading and scaling data science or engineering teams.
Experience leading teams focused on recommender systems, personalization, or behavioral modeling.
Experience designing Hidden Markov Models (HMMs), latent-state frameworks, or deep sequential models.
Strong background in A/B testing, quasi-experimental designs, or causal modeling to measure incremental impact.
Proven track record of deploying generative AI in production environments to personalize, explain, or enhance user recommendations.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
USA, WA, SEATTLE - 218,800.00 - 295,900.00 USD annually

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Keywords to mirror

aimlmachine learning

Platform: amazon
Effort: medium

Benefits

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Health Insurance

Dental

Vision

401(K)

Paid Time Off

Parental Leave