Senior Data Scientist , Alexa AI Aurora

Description

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.

Basic Qualifications

- 5 years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 4 years of data scientist experience
- Experience with statistical models e.g. multinomial logistic regression

Preferred Qualifications

- Experience managing data pipelines
- Experience as a leader and mentor on a data science team

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.