Senior Applied Scientist, Amazon Ads, Demand Tech , Amazon Advertising, Demand Tech

Amazon • Palo Alto, CA

8d • $167,100 - $260,000 • Onsite

About The Position

In Amazon Advertising, we apply Machine Learning at massive scale to optimize programmatic advertising performance. The Demand Tech team owns response prediction and incrementality models that power bid optimization across Amazon DSP and Sponsored Display — determining how billions of ad impressions are valued and served daily across Amazon-owned properties, the open internet, and third-party exchanges. We are looking for a talented Senior Applied Scientist to join our team of scientists and engineers working on high-impact prediction systems that directly drive advertiser KPIs (CPA, ROAS, incrementality) across endemic and non-endemic programmatic advertising.

Requirements

• 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

Nice To Haves

• 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.

Responsibilities

• Own end-to-end response prediction — design and improve deep learning models for multi-task prediction (click, conversion, page view, incrementality) serving at inference latencies under 10ms at millions of TPS
• Build and iterate on calibration mechanisms that keep prediction accuracy stable across rapidly shifting supply distributions
• Integrate novel signals (OpenRTB features, customer behavioral sequences, supply quality feeds) into production models to improve optimization quality
• Run online A/B experiments at scale, analyze results with statistical rigor, and translate offline gains into measurable business impact
• Collaborate closely with engineers on model serving infrastructure (SageMaker, GPU inference, real-time feature stores) to deploy models efficiently at scale
• Mentor scientists on the team and contribute to the broader Amazon ML science community through papers, conferences, and internal deep dives

Benefits

• 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
• parental leave
• sign-on payments
• restricted stock units (RSUs)

What This Job Offers

• Job Type: Full-time
• Career Level: Senior