Senior Applied Scientist, Advertising

About the role

Orchestrating the selection of one out of tens of millions of ads, honoring advertiser targeting intent for hundreds of thousands of advertisers while ensuring a great shopper experience for billions of shoppers millions of times per second on a latency of tens of milliseconds is not a trivial task. The demand retrieval team within the Amazon DSP organisation tackles this challenge by developing and operating machine learning models that match ad opportunities with the most relevant ads to deliver the right messages to the right customers at the right time. We are looking for an Applied Scientist to optimize ad matching for Amazon’s programmatic advertisement products. In this role you will lead the design and implementation of solutions for performance sourcing, using behavioural information on customers’ interactions with Amazon and other owned and operated businesses as well as contextual information about the bid request to predict their propensity to convert, driving better advertising campaign outcomes.

Responsibilities

• Design and implement deep learning models to match the right customers with the right ads across different verticals, geographies, and ad formats.
• Investigate new ML techniques such as multi‑task learning to ensure models can operate for a variety of advertisers in multiple industries and with different volumes of conversion events.
• Improve performance, generalisation, and scalability of models by introducing new features and enhancing model architecture.
• Work side‑by‑side with engineers to deliver code changes impacting the ads stack, handling very large datasets and high‑throughput production systems.
• Rapidly prototype and test many hypotheses/implementation alternatives in a high‑ambiguity environment, using quantitative analysis and business judgement.
• Partner with product and engineering teams, aligning on work, adjusting priorities based on business requirements, and iterating quickly on experiments.
• Apply a strong theoretical understanding of modern ML techniques and methodologies, and leverage software engineering and data‑processing skills to deploy them at Amazon‑scale.
• Stay immersed in Amazon’s advertisers and their objectives, thinking long‑term about turning those objectives into products and technical capabilities.
• Understand and contribute to the latest literature on machine learning for recommender and advertising systems, guiding strategic investment for the organization.

About the team

The Demand Retrieval team is responsible for designing, implementing, deploying, and operating machine learning models that match bid opportunities to ad demand based on performance, campaign delivery, and targeting objectives specified by advertisers. Success is measured through offline experimentation and online metrics that capture the impact of matching models on campaign KPIs such as cost per action, return on ad spend, budgets delivered, and targeting precision.

Basic 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 a 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.

Skills

• Strong software engineering and data‑processing abilities for large‑scale datasets.
• Proficiency in Java, C++, Python.
• Deep knowledge of neural networks, multi‑task learning, and other advanced ML techniques.
• Familiarity with distributed computing frameworks (Hadoop, Spark) and ML libraries (TensorFlow, MXNet, scikit‑learn).
• Ability to translate business objectives into technical solutions and product capabilities.

Benefits

• Comprehensive health insurance (medical, dental, vision, prescription).
• Basic Life & AD&D insurance with optional supplemental life plans.
• Employee Assistance Program and mental health support.
• Medical Advice Line.
• Flexible Spending Accounts.
• Adoption and surrogacy reimbursement coverage.
• 401(k) matching.
• Paid time off and parental leave.
• Sign‑on payments and restricted stock units (RSUs) as part of the compensation package.

Pay

USA, NY, New York – $183,800.00 – $248,700.00 USD annually. Final compensation will be determined based on experience, qualifications, and location, and includes sign‑on payments and RSUs.