Data Scientist, SPX AI Lab, SPX Science

Amazon.com Inc

Seattle, WA

JOB DETAILS
SKILLS
A/B Testing, Analysis Skills, Artificial Intelligence (AI), Best Practices, Business Growth, Computer Vision, Conversation Engine, Data Science, Economics, Machine Learning, Metrics, Natural Language Processing (NLP), Partner Sales, Performance Metrics, Problem Solving Skills, Product Planning, Product Strategy, Product/Service Launch, Reporting Dashboards, Research & Development (R&D), Revenue Growth, SPX, Sales, Scalable System Development, Scientific Research, Solution Sales, Statistical Modeling, Statistics, Strategic Analysis, Strategic Planning
LOCATION
Seattle, WA
POSTED
30+ days ago

The Selling Partner Experience (SPX) organization strives to make Amazon the best place for Selling Partners to do business. The SPX AI Lab team is building the AI capabilities powering the Selling Assistant, Amazon"s conversational assistant experience for Selling Partners. The Selling Assistant is a trusted partner and a seasoned advisor that's always available to enable our partners to thrive in Amazon's stores. It takes away the cognitive load of selling on Amazon by providing a single interface to handle a diverse set of selling needs. The assistant always stays by the seller"s side, talks to them in their language, enables them to capitalize on opportunities, and helps them accomplish their business goals with ease. It is powered by the latest advances in Generative AI, going beyond a typical chatbot to provide an intuitive, intelligent, agentic and personalized experience to sellers running real businesses, large and small.

Do you want to join an innovative group of scientists, engineers, and product managers who use advanced analytical, statistical, and machine learning techniques to help Amazon create a delightful Selling Partner experience? Are you excited about uncovering insights from massive-scale data, measuring the impact of AI-driven features, and shaping product strategy through rigorous analysis? Do you want to be part of one of Amazon's most strategic initiatives to understand and improve seller experience? If yes, the SPX AI Lab may be the perfect fit for you.

Key job responsibilities

    • Respond to Seller feedback and implement fix in Gen AI solution to enhance Seller experience
    • Drive deep-dive analytical studies to understand seller pain points, evaluate feature performance, and identify opportunities to improve the Selling Partner experience.
    • Design and execute robust causal inference and measurement frameworks, including A/B testing, quasi-experiments, and observational causal methods (e.g., diff-in-diff, synthetic control, propensity score methods).
    • Develop scalable analytical pipelines for impact measurement, KPI development, metric integrity validation, and long-term business monitoring.
    • Apply NLP and statistical modeling techniques-including topic modeling, clustering, semantic similarity, and classification-to uncover insights from unstructured seller interactions, feedback, and content.
    • Partner with scientists, engineers, economists, and product managers to translate ambiguous problems into structured analytical approaches and influence product roadmaps with data-driven recommendations.
    • Build and maintain automated analytics tools and dashboards to democratize insights for product, science, and engineering teams.
    • Collaborate scientists to evaluate model-driven features, quantify impact, and ensure mechanisms are grounded in rigorous measurement.
    • Research and experiment with new analytical and measurement methodologies, ensuring Amazon leverages the latest best practices in causal inference, NLP, and GenAI.

About the team

SPX AI Lab is a growing team of scientists driving the research and development of the next generation of GenAI experiences that empower Amazon"s Selling Partners to succeed. We draw from many science domains, from Natural Language Processing to Computer Vision to Optimization to Economics, to create solutions that seamlessly and automatically engage with Sellers, solve their problems, and help them grow. We strive to radically simplify the seller experience, lowering the cognitive burden of selling on Amazon by making it easy to accomplish critical tasks such as launching new products, understanding and complying with Amazon's policies and taking actions to grow their business.

About the Company

A

Amazon.com Inc

At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

It’s Always Day 1
At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

Our Leadership Principles
Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles
COMPANY SIZE
10,000 employees or more
INDUSTRY
Retail
FOUNDED
1994
WEBSITE
http://Amazon.com/militaryroles