At a Glance
- Tasks: Design and implement deep learning models to match ads with customers in real-time.
- Company: Join Amazon's innovative Demand Retrieval team, shaping the future of advertising.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment focused on innovation and collaboration.
- Why this job: Make a significant impact on billions of shoppers while working with cutting-edge technology.
- Qualifications: PhD or Master's in CS, ML experience, and programming skills in Java, C++, or Python.
The predicted salary is between 60000 - 80000 £ per year.
Orchestrating the selection of one ad 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 organization develops and operates machine learning models that match bid opportunities to ads based on performance, campaign delivery, and targeting objectives specified by advertisers.
Job 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 that models can operate for a variety of advertisers in multiple industries and with different volumes of conversion events.
- Improve the performance, generalisation, and scalability of models by introducing new features and enhancing model architectures.
- Work side by side with engineers to deliver code changes impacting the ads stack, working with very large datasets and high‑throughput production systems.
- Rapidly prototype and test many possible hypotheses/implementation alternatives in a high‑ambiguity environment, making use of both quantitative analysis and business judgment.
- Be immersed in Amazon’s advertisers and their objectives, thinking long‑term about how to turn those objectives into products and technical capabilities.
- Understand the latest literature on machine learning for recommender and advertising systems, contributing to guiding strategic investment for the organization.
Team Overview
The Demand Retrieval team is responsible for designing, implementing, deploying, and operating machine learning models that match bid opportunities to ads demand based on performance, campaign delivery, and targeting objectives specified by advertisers. Success is measured by offline experimentation and online metrics that reflect the impact of our matching models on campaign KPIs such as cost per action, return on ad investment, budgets delivered, and targeting precision.
Basic Qualifications
- PhD, or a Master’s degree and experience in CS, CE, ML, or related field research.
- Experience programming in Java, C++, Python, or related language.
- Experience building machine learning models for business application.
- Experience in state‑of‑the‑art deep learning model architecture design, training, optimization, and model pruning.
Preferred Qualifications
- Experience in retrieval and ranking systems as applied to advertising or recommender systems.
Applied Scientist, Advertising employer: Amazon Science
At Amazon, we pride ourselves on being an exceptional employer, particularly for the role of Applied Scientist in Advertising. Our innovative work culture fosters collaboration and creativity, allowing you to design cutting-edge machine learning models that impact billions of shoppers and hundreds of thousands of advertisers. With ample opportunities for professional growth and a commitment to diversity and inclusion, you'll thrive in an environment that values your contributions and encourages you to push the boundaries of technology.
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We think this is how you could land Applied Scientist, Advertising
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We think you need these skills to ace Applied Scientist, Advertising
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Amazon Science. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Amazon Science
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
