Sr. Manager, Applied Science, Sales AI - Amazon Ads (Advertising)

Amazon Inc.; Seattle (WA); On-site; USD 219,000 - 296,000; Full time

Job summary

Amazon.com Services LLC is seeking an experienced science leader to build and guide a team of applied scientists focused on advertiser growth, delivering personalized recommendations that help brands grow. You will own the multi-year roadmap and collaborate with product and engineering.

You will hire and develop top talent, set high scientific standards, and translate research into production-quality models that inform business decisions across teams.

Qualifications

• 10+ years applying ML to large-scale problems
• Experience distilling customer requirements into problem definitions
• Experience hiring and developing scientists and mentoring junior members
• Experience setting science strategy across multiple teams
• PhD or Master's in CS, ML, or related field, or equivalent applied research

Responsibilities

• Set the long-term scientific vision for modeling advertiser growth journeys
• Guide the integration of signals into personalized recommendations
• Hire, coach, and develop scientists and engineers
• Partner with product and engineering to productionize models
• Set quality standards and make critical trade-off decisions

Skills

ML for large-scale problems

Lead and mentor scientists

Define research direction

Cross-functional collaboration

Python & ML frameworks

Education

PhD or Master's in CS/ML

Tools

Python

TensorFlow

PyTorch

Job description

Job ID: 10568165 | Amazon.com Services LLC

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

• 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.

Basic Qualifications

• 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

Preferred Qualifications

• 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 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.

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 https://amazon.jobs/en/benefits.

USA, WA, SEATTLE - 218,800.00 - 295,900.00 USD annually