Data Scientist

About the Role

Join Alexa Connections as a Data Scientist and spearhead the development of advanced machine learning and data science solutions. Your work will be pivotal in enhancing intelligent communication experiences across various channels, including calling, messaging, and email. You'll collaborate closely with product, engineering, and business leaders to transform complex, ambiguous challenges into scalable machine learning models, robust experimentation frameworks, and insightful data-driven product strategies.

In this dynamic role, you will be responsible for designing and deploying sophisticated ML and statistical models for critical functionalities such as prioritization, intent detection, and proactive action recommendations. You will analyze extensive datasets and conduct rigorous experiments, including A/B testing and causal analysis, to accurately measure impact and drive continuous improvements in customer engagement and product performance.

Furthermore, you will play a key role in shaping the applied science roadmap and work collaboratively with global, cross-functional teams to deliver AI-driven solutions that cater to millions of Alexa customers worldwide.

Key Responsibilities

• Collaborate with product, engineering, operations, and security teams to translate intricate business problems into production-ready data science and ML solutions.
• Manage the complete lifecycle of model development, from initial exploratory analysis and model design to deployment, monitoring, and ongoing optimization.
• Define and track key success metrics, perform thorough analyses, and provide actionable insights to inform product launches, feature enhancements, and data-driven decision-making.
• Develop compelling business cases supported by data to prioritize science initiatives and effectively demonstrate the measurable impact of ML solutions.
• Build and deploy ML-powered systems that support core business functions.
• Lead research and analysis efforts focused on understanding customer interactions with Alexa to enhance the overall customer experience.
• Contribute to the broader science community through mentoring analysts, enhancing data workflows and tooling, and disseminating technical findings through internal and external publications.

A Day in the Life

• Conduct in-depth analysis of business metrics, identifying trends and reviewing performance dashboards.
• Write code for building Python packages, crafting SQL queries, and deploying solutions for consumption by Connections experience teams.
• Participate in or lead working sessions with Product Managers to refine problem statements and define new initiatives.
• Explore innovative features and model architectures, utilizing AWS services and documentation, while continuously upskilling with the latest technologies.
• Leverage pre-trained Large Language Models (LLMs) to develop applications that address business challenges within Connections experiences.
• Engage in meetings with Senior/Principal Engineers to align on solution designs.
• Contribute to or own Monthly/Weekly Business Review (MBR/WBR) documents for review with the Connections leadership team.

Basic Qualifications

• Minimum of 2 years of experience as a Data Scientist.
• 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).
• Minimum of 3 years of experience with machine learning/statistical modeling data analysis tools and techniques, and understanding parameters affecting their performance.
• Minimum of 1 year of experience creating or contributing to mathematical textbooks, research papers, or educational content.

Preferred Qualifications

• Ph.D. in a Science, Technology, Engineering, or Mathematics (STEM) field.
• Solid understanding of machine learning concepts and their application to reasoning and problem-solving.
• Proficiency in Python, Perl, or another scripting language.
• Previous experience in a Machine Learning or Data Scientist role at a major technology company.
• Experience in defining and creating benchmarks for evaluating the performance of Generative AI (GenAI) models.
• Proven experience working on multi-team, cross-disciplinary projects.
• Demonstrated ability to apply quantitative analysis to solve business problems and make data-driven decisions.
• Skill in effectively communicating complex concepts both verbally and in writing.