Sr. Applied Scientist, Search Data Science

Amazon is one of the most popular sites in the US. Our product search engine, one of the most heavily used services in the world, indexes billions of products and serves hundreds of millions of customers world-wide.

Our team leads the science and analytics efforts for the search page and we own multiple aspects of understanding how we can measure customer satisfaction with our experiences.

This include building science based insights and novel metrics to define and track customer focused aspects.

We are working on a new measurement framework to better quantify and qualify the quality of the search customer experience and are looking for a Senior Applied Scientist to lead the development and implementation of different signals for this framework and tackle new and uncharted territories for search engines.

This includes very ambiguous areas of quality where we would like to measure how customers perceive the results and take action to improve it.

Key job responsibilities

We are looking for an experienced Sr. Applied Scientist to lead signal development with an LLM influence and drive critical product decisions for Amazon Search.

We are developing new ways we measure customer satisfaction with the quality of the search page including translating their perception into large scale quantitative metrics.

LLMs will be one powerful tool in our toolkit. You will design and build AI based science solutions to allow routine inspection and deep business understanding as the search customer experience is being transformed.

These metrics and signals will be made available for downstream teams to use as features in their decision making model or optimization systems.

Your desire to learn and be curious will help us look around corners for improvement opportunities and more efficient metrics development.

In this role, you will partner with data engineers, business intelligence engineers, product managers, software engineers, economists, and other scientists.

About the team

The mission of the Search Data Science team is to build a world class shopping experience that delights customers. We focus on the long term and big picture, ensuring that the search page is balancing strategic trade-offs.

We bring to this effort expertise in constrained optimization, causal inference, and marketplace equilibrium effects. We build systems, metrics, and mechanisms to ensure that product decisions are scientifically sound.

We develop models to estimate the downstream dollar value of the quality of the experience. We spend time on evaluating experiments to develop durable learnings.

BASIC QUALIFICATIONS

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

PREFERRED QUALIFICATIONS

• Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
• Experience with popular deep learning frameworks such as MxNet and Tensor Flow.
• Experience with fine tuning Large Language Models and Retrieval-Augmented Generation is advantageous
30+ days ago