Applied Scientist, Sponsored Products

Amazon; Arlington (VA); On-site; USD 143,000 - 193,000; Full time

Job summary

Amazon.com Services LLC in Arlington, VA is seeking an Applied Scientist to drive end-to-end ML projects, building and deploying models for ads and shopping experiences. You will work with software engineers to productionize models, run A/B tests, and generate insights from massive datasets to improve monetization and sales.

The role emphasizes GenAI focus, scalable analytics, and collaboration with cross-functional teams to shape future advertising technologies across Amazon’s Retail and

Qualifications

• 3+ years of building models for business application experience.
• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience.
• Experience programming in Java, C++, Python or related language.
• Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high‑performance computing.

Responsibilities

• Drive end-to-end Machine Learning projects with ambiguity, scale, and complexity.
• Analyze and model large data sets to improve traffic monetization and merchandise sales while preserving shopper experience.
• Build, test, validate, and deploy ML models in production with software engineers.
• Run A/B experiments, collect data, and perform statistical analysis.
• Create scalable, automated processes for big data analysis and model development.
• Research new and innovative ML approaches.

Skills

Java

C++

Python

Algorithms & Data Structures

Numerical Optimization

Data Mining

Parallel & Distributed Computing

High-Performance Computing

Building models for business应用

Education

PhD or MS with CS/CE/ML background

Job description

Description

About Sponsored Products and Brands

The Sponsored Products and Brands team at Amazon Ads is re‑imagining the advertising landscape through 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.

About Our Team

The SPB Offsite team builds solutions to extend campaigns to reach customers off the store and extend shopping experiences on third party sites where shoppers search and discover products. We use industry leading machine learning, high-scale low latency systems, and AI technologies to create better sponsored customer experiences off the store. This role will have deep interest in building the next innovations in ad tech and shopping wherever shoppers go. You will work with external and internal partners to connect ad tech systems, understand customers, and drive results at scale. You are a deeply technical leader who operates with a GenAI first approach to product, engineering, and science based solutions.

As An Applied Scientist On This Team, You Will

• Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.
• Perform hands‑on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience.
• Build machine learning models, perform proof‑of‑concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.
• Run A/B experiments, gather data, and perform statistical analysis.
• Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
• Research new and innovative machine learning approaches.

Why you will love this opportunity: Amazon is investing heavily in building a world‑class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long‑term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world‑class products. We are a highly motivated, collaborative, and fun‑loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate.

Impact and Career Growth: You will invent new experiences and influence customer‑facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest‑growing businesses across all of Amazon! Define a long‑term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.

Basic Qualifications

• 3+ years of building models for business application experience
• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
• Experience programming in Java, C++, Python or related language
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high‑performance computing

Preferred Qualifications

• Experience in professional software development
• Experience in search advertising, search marketing, performance advertising, or similar digital advertising
• Strong technical fluency in Generative AI
• Deep understanding of large language models (LLMs), model fine tuning and prompt engineering
• Ph.D. in computer science, mathematics, statistics, machine learning or equivalent quantitative field

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, NY, New York - 172,400.00 - 223,400.00 USD annually

USA, VA, Arlington - 142,800.00 - 193,200.00 USD annually

USA, WA, SEATTLE - 142,800.00 - 193,200.00 USD annually

Company

Amazon.com Services LLC

Job ID: A10385985