Data Scientist, Alexa Connections
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As a Data Scientist in Alexa Connections, you will lead the end-to-end development of machine learning and data science solutions that power intelligent communication experiences across channels such as calling, messaging and email. You will partner closely with product, engineering, and business leaders to translate ambiguous problems into scalable ML models, experimentation frameworks, and data-driven product decisions. In this role, you will design and deploy advanced ML and statistical models for capabilities such as prioritization, intent detection, and proactive action recommendations. You will analyze large-scale datasets and run rigorous experiments, including A/B testing and causal analysis, to measure impact and continuously improve customer engagement and product performance. Additionally, you will shape the applied science roadmap and collaborate with global cross-functional teams to deliver AI-driven solutions that scale to millions of Alexa customers.
Key job responsibilities
- Partner with product, engineering, operations, and security teams to translate complex business problems into scalable, production-ready data science and ML solutions.
- Own the full lifecycle of model development, including exploratory analysis, model design, deployment, monitoring, and continuous improvement.
- Define and track success metrics, conduct rigorous analyses, and provide insights that guide product launches, feature improvements, and data-driven decision-making.
- Build data-driven business cases to prioritize science initiatives and demonstrate measurable impact of ML solutions.
- Develop ML-powered systems supporting key business areas.
- Lead research and analysis to understand customer interactions with Alexa, and enhance overall customer experience.
- Contribute to the broader science community by mentoring analysts, improving data workflows and tooling, and publishing technical work in internal and external forums.
A day in the life
• Deep dive into our business metrics, analyze data, trends, and reviewing dashboards
• Writing code: building packages in Python, writing SQL queries, deploying solutions for Connections experience teams to consume.
• Leading or joining working sessions with Product Managers to refine problem statements new initiatives.
• Exploring new features and model architectures, leveraging AWS services, documentation, and upskilling yourself to the latest technologies.
• Leverage pre-trained LLMs to build applications that solve business problems for Connections experiences.
• Meet with Sr. Engineers/Principal Engineers to align on solution designs.
• Own or co-own MBR, WBR documents that are reviewed with Connections leadership team.
Key job responsibilities
- Partner with product, engineering, operations, and security teams to translate complex business problems into scalable, production-ready data science and ML solutions.
- Own the full lifecycle of model development, including exploratory analysis, model design, deployment, monitoring, and continuous improvement.
- Define and track success metrics, conduct rigorous analyses, and provide insights that guide product launches, feature improvements, and data-driven decision-making.
- Build data-driven business cases to prioritize science initiatives and demonstrate measurable impact of ML solutions.
- Develop ML-powered systems supporting key business areas.
- Lead research and analysis to understand customer interactions with Alexa, and enhance overall customer experience.
- Contribute to the broader science community by mentoring analysts, improving data workflows and tooling, and publishing technical work in internal and external forums.
A day in the life
• Deep dive into our business metrics, analyze data, trends, and reviewing dashboards
• Writing code: building packages in Python, writing SQL queries, deploying solutions for Connections experience teams to consume.
• Leading or joining working sessions with Product Managers to refine problem statements new initiatives.
• Exploring new features and model architectures, leveraging AWS services, documentation, and upskilling yourself to the latest technologies.
• Leverage pre-trained LLMs to build applications that solve business problems for Connections experiences.
• Meet with Sr. Engineers/Principal Engineers to align on solution designs.
• Own or co-own MBR, WBR documents that are reviewed with Connections leadership team.