Sr. Data Scientist , Companion Product & Servi (ComPAS)

Amazon.com Inc

Seattle, WA

JOB DETAILS
SKILLS
A/B Testing, Analysis Skills, Artificial Intelligence (AI), Automation, Business Case, Consumer Marketing, Continuous Deployment/Delivery, Continuous Improvement, Cross-Selling, Customer/Consumer Behavior, Data Analysis, Data Science, Establish Priorities, Finance, Market Segmentation, Marketing, Mentoring, Pricing, Problem Solving Skills, Product Marketing, Product Pricing, Prototyping, Python Programming/Scripting Language, SQL (Structured Query Language), Scientific Publications, Stress Modeling, Stress Testing, Target Marketing, Technical Publications, Workflow Analysis
LOCATION
Seattle, WA
POSTED
4 days ago

ComPAS Business Insights sits at the intersection of pricing, marketing, and consumer science for Amazon"s Companion Products & Services portfolio; spanning Accessories, Pre-Owned Business (POB), and Trade-In (TI). AI is fundamentally changing how we solve these problems. As a Sr. Data Scientist, you will drive that transformation: building advanced ML models and AI-powered tools that automate decision science at scale, turning complex pricing, targeting, and segmentation challenges into intelligent, self-improving systems.

You will partner with product, marketing, finance, and engineering leaders to translate ambiguous problems into production-ready ML systems and AI-powered tools. Your work will span pricing science, consumer behavior analysis, marketing targeting, propensity score development, and customer segmentation - always with an eye toward how generative AI and foundation models can accelerate, scale, or reimagine the solution.

Key job responsibilities

Key Job Responsibilities

  • Own the full lifecycle of model development - from problem framing and exploratory analysis through feature engineering, model design, deployment, and continuous improvement.
  • Oversees the development of pricing science models, including price elasticity estimation, promotional effectiveness measurement, and optimal pricing recommendations across Accessories, POB, and TI product lines.
  • Build and refine propensity models and customer segmentation frameworks that enable precision marketing targeting and personalized customer engagement.
  • Conduct consumer behavior analysis to uncover purchase patterns, cross-sell opportunities, and drivers of performance across the ComPAS portfolio.
  • Leverage generative AI and LLMs (e.g., Amazon Bedrock, foundation models) to build intelligent tools that automate insights generation, scale analytical workflows, and solve problems that were previously intractable.
  • Identify and execute opportunities to optimize and automate existing analytical and scientific processes -ntransforming manual, repetitive work into scalable AI-powered pipelines.
  • Design and run rigorous experiments (A/B testing, causal inference, synthetic control) to measure impact and guide strategic decisions on pricing, marketing, and product.
  • Build data-driven business cases to prioritize science and AI initiatives, demonstrating measurable impact on revenue and customer outcomes.
  • Contribute to the broader science community by mentoring data scientists and publishing technical work in internal and external forums.

A day in the life

Your mornings start with decision science - framing a pricing or targeting problem, writing Python/SQL to prototype a model, or stress-testing a segmentation approach. Afternoons shift to AI tool-building: experimenting with foundation models, designing automation pipelines, or collaborating with engineers on deployment architecture. Between deep work blocks, you"re leading problem-framing sessions with PMs, and business leaders, demoing AI prototypes to stakeholders, or hosting a Lunch & Learn that sparks the next automation idea across the team.

About the team

ComPAS Business Insights is the AI-first data science and analytics team powering Amazon"s Companion Products & Services portfolio - Accessories, Pre-Owned Business (POB), and Trade-In (TI). We own the full stack: from production-grade data infrastructure and automated reporting to advanced decision science spanning pricing, consumer behavior, marketing targeting, segmentation, and propensity modeling. We are leveraging AI to build intelligent tools that automate workflows, democratize insights, and put self-service analytics at stakeholders" fingertips. Our mission: turn every pricing, marketing, and customer decision into a science-powered, AI-accelerated outcome.

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