Senior Data Scientist, ADE Science

Amazon

Amazon

Data Science
Vancouver, BC, Canada
Posted on Dec 6, 2025

Description

The Alexa Daily Essentials team delivers experiences critical to how customers interact with Alexa as part of daily life. Alexa users engage with our products across experiences connected to Timers, Alarms, Calendars, Food, and News. Our experiences include critical time saving techniques, ad-supported news audio and video, and in-depth kitchen guidance aimed at serving the needs of the family from sunset to sundown.

As a Data Scientist on our team, you'll work with complex data, develop statistical methodologies, and provide critical product insights that shape how we build and optimize our solutions. You will work closely with your Analytics and Applied Science teammates. You will build frameworks and mechanisms to scale data solutions across our organization. If you are passionate about redefining how AI can improves everyone's daily life, we’d love to hear from you.

Key job responsibilities
Problem-Solving

- Analyze complex data (including healthcare data, experimental data, and large-scale datasets) to identify patterns, inform product decisions, and understand root causes of anomalies.
- Develop analysis and modeling approaches to drive product and engineering actions to identify patterns, insights, and understand root causes of anomalies. Your solutions directly improve the customer experience.
- Independently work with product partners to identify problems and opportunities. Apply a range of data science techniques and tools to solve these problems. Use data driven insights to inform product development. Work with cross-disciplinary teams to mechanize your solution into scalable and automated frameworks.

Data Infrastructure

- Build data pipelines, and identify novel data sources to leverage in analytical work - both from within Alexa and from cross Amazon
- Acquire data by building the necessary SQL / ETL queries

Communication

- Excel at communicating complex ideas to technical and non-technical audiences.
- Build relationships with stakeholders and counterparts. Work with stakeholders to translate causal insights into actionable recommendations
- Force multiply the work of the team with data visualizations, presentations, and/or dashboards to drive awareness and adoption of data assets and product insights
- Collaborate with cross-functional teams. Mentor teammates to foster a culture of continuous learning and development