Senior Data Scientist , Alexa AI Aurora

Amazon.com Inc

Bellevue, WA

JOB DETAILS
SKILLS
Amazon Alexa, Analysis Skills, Architectural Services, Artificial Intelligence (AI), Best Practices, Business Processes, Communication Skills, Computer Vision, Customer Experience, Data Management, Data Science, Leadership, Machine Learning, Mentoring, Metrics, Modeling Languages, Natural Language Processing (NLP), Platform for Privacy Preferences, Presentation/Verbal Skills, Problem Solving Skills, Quality Assurance, Sales Prospecting, Systems Scalability, Team Player, Technical Delivery, Technical Presentation, Technical Writing, Test Automation
LOCATION
Bellevue, WA
POSTED
30+ days ago

The Alexa AI AURORA organization is seeking a passionate, talented, and resourceful Senior Data Scientist to define and solve complex, ambiguous problems in state-of-the-art conversational AI. You will lead large-scale data science initiatives across the fields of Large Language Models (LLMs), Natural Language Processing (NLP), and Artificial Intelligence (AI), selecting the ideal methodologies from a wide range of data science disciplines to drive measurable business impact for millions of Alexa customers.

In this role, you will autonomously define problem spaces and solution approaches, working closely with business, science, and engineering teams to build consensus and influence strategy. You will advise senior leadership on data-driven decisions, identify blind spots in existing metrics, and propose new measurements that shape our product direction. You will actively mentor and develop other data scientists while setting standards for scientific rigor and operational excellence within the team.

The ideal candidate has broad expertise across multiple data science disciplines and a deep understanding of how software systems, data pipelines, and business processes interact. They take the lead on complex projects with minimal guidance, make sound trade-offs between short-term customer needs and long-term technical investments, and deliver solutions that are scalable, reproducible, and actionable. A proven track record of launching data science solutions that drive significant business outcomes is essential. Strong communication skills, the ability to document and present technical findings to both technical and non-technical audiences, and a commitment to collaborative teamwork are absolute requirements.

Join us in shaping the future of Generative AI and delivering unparalleled experiences for Alexa customers worldwide.

Key job responsibilities

Define the data science strategy for conversation modelling, content generation, and automated quality assurance by evaluating a wide range of methodologies across machine learning, generative AI, and computer vision, recommending the right approach based on business needs and scientific rigor.

Lead the design and end-to-end delivery of complex, ambiguous data science initiatives from problem formulation through experimentation to production deployment, autonomously defining the problem space, selecting ideal solution approaches, and driving measurable business outcomes.

Make high-judgment trade-offs across audio, text, and visual quality dimensions, balancing short-term customer needs against long-term platform extensibility, cost efficiency, and scalability while quantifying the impact of each decision.

Establish evaluation frameworks, metrics, and success criteria for the team"s scientific initiatives, identifying blind spots in existing measurements and proposing new mechanisms that institutionalize rigorous validation across customer touch points.

Identify new business opportunities by staying at the forefront of AI/ML advances, translating emerging techniques into actionable data science directions with clear, quantifiable customer and business impact.

Drive consensus across multiple teams on the architectural and methodological decisions underlying scalable agentic systems for conversation understanding and generation, ensuring alignment between data, software systems, and business processes.

Set and continuously raise the bar for data science best practices across the team, creating models and analyses that are actionable, reproducible, and easy for others to contribute to and extend.

Tackle the team"s most complex technical problems, applying broad expertise across multiple data science disciplines while maintaining practical focus on solution generalizability and customer value.

Actively mentor and develop other data scientists in the organization, leading scientific reviews, providing constructive feedback on methodology and results, and keeping the team current on data science advancements.

Advance the team"s scientific reputation through high-impact publications and presentations at top-tier venues, and generate intellectual property through patents.

About the team

AURORA is the AI runtime backbone and horizontal intelligence team that powers Alexa"s core infrastructure, AI capabilities, and specialized conversational models. We revolutionize conversational AI through three core pillars: architecting mission-critical AI runtime systems, advancing science solutions that connect key conversational capabilities, and transforming how builders create at scale. We empower 1P and 3P engineers and scientists worldwide with modular, reusable platforms that accelerate innovation while delivering accurate, responsive, and reliable conversational experiences to millions of end-users through operational excellence at scale.

About the Company

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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