Data Scientist

Role Overview

As a Data Scientist in Alexa Connections, you will be instrumental in the complete development of machine learning and data science solutions that enhance intelligent communication experiences across various channels, including calling, messaging, and email. You will collaborate closely with product, engineering, and business leaders to transform complex, undefined problems into scalable machine learning models, robust experimentation frameworks, and data-driven product strategies. This role involves designing and deploying advanced machine learning and statistical models for key capabilities such as prioritization, intent detection, and proactive action recommendations. You will analyze large-scale datasets and conduct rigorous experiments, including A/B testing and causal analysis, to quantify impact and drive continuous improvements in customer engagement and product performance. Furthermore, you will contribute to shaping the applied science roadmap and work with global, cross-functional teams to deliver AI-driven solutions that serve millions of Alexa customers.

Key Responsibilities

• Collaborate with product, engineering, operations, and security teams to translate intricate business challenges into scalable, production-ready data science and ML solutions.
• Oversee the entire lifecycle of model development, encompassing exploratory analysis, model design, deployment, monitoring, and ongoing refinement.
• Define and monitor success metrics, perform in-depth analyses, and deliver insights to inform product launches, feature enhancements, and data-driven decision-making.
• Develop data-driven business cases to prioritize scientific initiatives and demonstrate the measurable impact of ML solutions.
• Build ML-powered systems to support critical business areas.
• Lead research and analysis to understand customer interactions with Alexa and improve the overall customer experience.
• Contribute to the broader scientific community through mentoring analysts, enhancing data workflows and tooling, and publishing technical work internally and externally.

A Day in the Life

• Conduct deep dives into business metrics, analyze data and trends, and review dashboards.
• Write code, including building Python packages, executing SQL queries, and deploying solutions for Connections experience teams.
• Lead or participate in working sessions with Product Managers to refine problem statements and explore new initiatives.
• Explore new features and model architectures, utilizing AWS services, documentation, and continuously upskilling in the latest technologies.
• Leverage pre-trained Large Language Models (LLMs) to develop applications that address business problems for Connections experiences.
• Meet with Senior and Principal Engineers to align on solution designs.
• Own or co-own Monthly Business Review (MBR) and Weekly Business Review (WBR) documents for review with the Connections leadership team.

Basic Qualifications

• A minimum of 2 years of experience as a Data Scientist.
• A minimum of 3 years of experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical/mathematical software (e.g., R, SAS, Matlab).
• A minimum of 3 years of experience with machine learning/statistical modeling, data analysis tools, techniques, and parameters affecting their performance.
• A minimum of 1 year of experience creating or contributing to mathematical textbooks, research papers, or educational content.

Preferred Qualifications

• A Ph.D. in Science, Technology, Engineering, or Mathematics (STEM).
• Proficiency in machine learning concepts and their application to reasoning and problem-solving.
• Experience in Python, Perl, or another scripting language.
• Experience in a machine learning or data scientist role within a large technology company.
• Experience in defining and creating benchmarks for assessing Generative AI model performance.
• Experience working on multi-team, cross-disciplinary projects.
• Experience applying quantitative analysis to solve business problems and making data-driven business decisions.
• Proven ability to effectively communicate complex concepts through written and verbal communication.

Inclusive Culture and Accommodations

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and require workplace accommodations or adjustments during the application and hiring process, including support for interviews or onboarding, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If your country/region is not listed, please contact your Recruiting Partner.