Manager, Applied Science, AB Marketing Tech

Amazon is hiring a Manager, Applied Science, AB Marketing Tech in Seattle, United States. It pays $184k-$249k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

On Level's scale, this marketing role is Builds AI ●●●●: the job is building AI systems.
The listed pay starts 26% above the typical marketing posting on Level.
Tools and skills the posting cites include computer vision, NLP and machine learning.
Level classifies it as a lead role.
Level lists 20,000+ other open roles at Amazon.

AI in this role

Lead applied science teams and machine learning predictive modeling strategies for Amazon Business marketing and growth.

computer-visionnlpmachine-learningpredictive-modelingteam-leadershipscience-strategy

Come be a part of a rapidly expanding $35 billion dollar global business. At Amazon Business, a fast-growing startup passionate about building solutions, we set out every day to innovate and disrupt the status quo. We stand at the intersection of tech & retail in the B2B space developing innovative purchasing and procurement solutions to help businesses and organizations thrive. At Amazon Business, we strive to be the most recognized and preferred strategic partner for smart business buying. Bring your insight, imagination and a healthy disregard for the impossible. Join us in building and celebrating the value of Amazon Business to buyers and sellers of all sizes and industries. Unlock your career potential.

The Opportunity

This is one of the most consequential science leadership roles in Amazon Business. As Applied Science Manager, you will directly influence over $40B in annual revenue by owning the science strategy that powers how we acquire, engage, monetize, and retain millions of business customers worldwide. Your models won't sit in notebooks. They will run in production, shaping real-time decisions across the full customer lifecycle for one of Amazon's fastest-growing businesses.

You will operate at the intersection of Business Prime, Marketing Science, and Customer Acquisition three of the highest-visibility, highest-impact charters in the organization. Your work will be presented to VPs and SVPs, inform multi-billion-dollar investment decisions, and fundamentally reshape how Amazon Business goes to market. This is not an incremental optimization role. This is a build-the-future role where your science roadmap becomes the business strategy.

What You'll Own

Team Leadership & Talent Development: Build and lead a world-class team of applied scientists and research scientists. Set the technical vision, define the multi-year science roadmap, and create an environment where scientists ship models that move the needle on $40B+ in revenue. You will be the bar-raiser who attracts top talent and develops the next generation of science leaders at Amazon.

Customer Lifecycle Intelligence ($40B+ Revenue Impact): Own the predictive modeling stack that powers customer identification, targeting, spend behavior forecasting, churn propensity, and declining engagement detection across every Business Prime segment. Your models will determine which customers we invest in, how we invest, and when directly impacting billions in customer lifetime value.

Marketing Science & Measurement (Cross-Functional, Multi-Billion Dollar Allocation): Build the causal inference and attribution frameworks that determine how Amazon Business allocates hundreds of millions in marketing investment across paid, owned, and earned channels globally. You will be the single point of science truth for incrementality measurement, marketing mix modeling, and ROI optimization partnering with Marketing, Finance, CPS, and international teams to ensure every dollar drives maximum impact.

Customer Acquisition Engine: Lead the science that accelerates new Business Prime member acquisition at scale. Build propensity models, audience optimization systems, and channel effectiveness frameworks that feed directly into acquisition engines serving 10+ global markets. Your work will be the difference between linear growth and exponential growth.

Benefits Adoption & the "Aha Moment": Build behavioral segmentation and recommendation systems that identify, for each customer vertical and organizational profile, the exact moment and feature combination that converts a trialist into a loyalist. This is the science of delight at scale.

Trust & Safety at Scale: Develop fraud detection models, abuse identification systems, and eligibility classifiers that protect the integrity of the Business Prime ecosystem safeguarding billions in revenue from bad actors.

Experimentation & Causal Inference (Organization-Wide): Establish the experimentation frameworks and causal inference methodologies used across the entire Amazon Business organization. Design experiments that measure incremental impact of product launches, pricing changes, and marketing interventions creating the scientific foundation for how leadership makes high-stakes decisions.

Why This Role Is Different

This is not a role where you optimize a feature in isolation. You will sit at the center of a complex, cross-functional operating model partnering daily with 7+ senior leaders (including Directors and VPs) across Business Prime, CPS Sales, Central Marketing, SSR, GTMO, Finance, and International teams. Your science will be the connective tissue that aligns these organizations around a shared, data-driven growth strategy.

You will have direct senior leadership visibility — presenting findings, recommendations, and roadmaps to VP audiences regularly. The insights your team generates will shape OP1/OP2 planning, Board-level narratives, and multi-year investment theses.

What We're Looking For

The successful Applied Science Manager will have an bias for action in a startup environment, with people leadership skills, a proven ability to build and manage high-performing science teams, define and prioritize research agendas that map to business outcomes, and build methodology and tools that are statistically grounded. You influence product and business strategy through science translating complex analytical findings into crisp, actionable recommendations that senior leaders act on immediately.

We are seeking someone who thrives in a fast-paced, high-energy, and fun work environment where we deliver value incrementally and frequently. You are a highly technical leader who knows your subject matter deeply, can elevate the technical bar of your team, and is energized by ambiguity and new problem spaces. You know how to deliver results and show a desire to develop yourself, your colleagues, and your career.

Basic qualifications

- 3+ years of scientists or machine learning engineers management experience
- Knowledge of ML, NLP, Information Retrieval and Analytics

Preferred qualifications

- 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

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 - 183,800.00 - 248,700.00 USD annually

How we rate this

Manager, Applied Science, AB Marketing Tech at Amazon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Manager, Applied Science, AB Marketing Tech is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $184k-$249k a year.
The role is based in US, WA, Seattle.
The job was posted on September 9, 2026.
Seniority: lead.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Computer visionNLPMachine learningPredictive ModelingTeam LeadershipScience Strategy

Also common in marketing jobs at this level

Python LLM Spark Generative AI SQL AWS

Pay

This job starts at: $184k
Typical marketing job: $146k

This posting starts 26% above the typical marketing job. See marketing jobs

Questions you could be asked

Walk me through a computer vision problem you solved, from raw data to a deployed model.
What NLP problem have you worked on, and how did you measure whether it actually worked?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where predictive modeling was part of your work. What did you do?
Tell me about a project where team leadership was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Computer vision, NLP, Machine learning, Predictive Modeling, and Team Leadership. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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