Senior Applied Scientist , Sponsored Products and Brands Ads Response Prediction

Amazon; Omaha, Northern (NE, KY); Hybrid; USD 167,000 - 260,000; Full time

Job summary

Amazon is seeking a Senior Applied Scientist for Sponsored Products and Brands Ads Response Prediction to build and deploy advanced machine-learning models. You will lead data-driven analyses, design experiments, and work with software engineers to ship end-to-end solutions that improve ad response and bidding dynamics.

The role emphasizes GenAI explorations, scalable ML pipelines, and collaboration across SPB teams to enhance personalization across placements and devices worldwide.

Qualifications

• 3+ years of building machine learning models for business applications.
• PhD or Master's degree with 6+ years of applied research experience.
• Experience programming in Java, C++, Python or related language.

Responsibilities

• Conduct deep data analysis to derive insights and identify opportunities.
• Develop scalable ML models and optimization strategies to solve business problems.
• Run regular A/B experiments, gather data, and perform statistical analysis.
• Collaborate with software engineers to deliver end-to-end production solutions.
• Improve scalability, efficiency and automation of large-scale data analytics and model deployment.
• Research new ML and GenAI approaches to optimize SPB ads.

Skills

Java

C++

Python

Deep learning

Education

PhD or Master's + 6+ years

Tools

TensorFlow

PyTorch

scikit-learn

Spark

Job description

Senior Applied Scientist , Sponsored Products and Brands Ads Response Prediction

Job ID: 10547666 | Amazon.com Services LLC

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.

Key job responsibilities

• Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities
• Develop scalable and effective machine-learning models and optimization strategies to solve business problems
• Run regular A/B experiments, gather data, and perform statistical analysis
• Work closely with software engineers to deliver end-to-end solutions into production
• Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving
• Conduct research on new machine-learning modeling and Generative AI solutions to optimize all aspects of Sponsored Products and Brands business

About the team

The Ad Response Prediction team within Sponsored Products and Brands (SPB) drives personalized shopping experiences for SPB Ads across placements, pages, and devices worldwide. We achieve this through ML and GenAI solutions that include customized shopper response prediction and session-level understanding to optimize every stage of the ad-serving process, from sourcing and bidding to widget discovery and auctions. Our responsibilities include advancing response prediction through model and feature innovations and extending prediction beyond the auction stage to areas such as targeting, sourcing, and bidding.

Basic Qualifications

• 3+ years of building machine learning models for business application experience
• PhD, or Master's degree and 6+ years of applied research experience
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning

Preferred Qualifications

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
• Experience with large scale distributed systems such as Hadoop, Spark etc.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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 .

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