Data Scientist, ADE Analytics – Amazon – Vancouver, BC

Vancouver’s tech scene is home to some of the most exciting AI and product work in the world, and Amazon’s Alexa Daily Essentials (ADE) Analytics team is right at the centre of it. This Data Scientist role offers the chance to shape how millions of people interact with Alexa every single day — from timers and alarms to food guidance and news experiences. If you thrive on turning complex data into real product impact, this position in Vancouver, BC is worth a serious look.

Working alongside Analytics and Applied Science teammates, you’ll develop statistical methodologies, build scalable data frameworks, and deliver insights that directly influence how the team builds and optimises Alexa experiences. This is hands-on, cross-functional work that blends data infrastructure, product analytics, and stakeholder communication in equal measure.

About the Role: Data Scientist, ADE Analytics

The Alexa Daily Essentials team is responsible for customer experiences tied to Timers, Alarms, Calendars, Food, and News — features that people rely on throughout their day. As a Data Scientist on this team, your work will span problem-solving, data pipeline development, and translating complex findings into clear, actionable recommendations for both technical and non-technical audiences.

You’ll collaborate with cross-functional partners including product managers and engineers, contribute to a culture of continuous learning by mentoring teammates, and help scale data solutions across the organisation. The role sits within Amazon’s Machine Learning (MLS) discipline and requires someone who is as comfortable building SQL/ETL pipelines as they are presenting insights to senior stakeholders.

Benefits and Salary

The base salary range for this position is $85,200 to $142,300 CAD annually, depending on experience, qualifications, and location. Amazon’s total compensation package may also include sign-on payments and Restricted Stock Units (RSUs). Benefits include comprehensive health insurance (medical, dental, vision, prescription, basic life and AD&D), a Registered Retirement Savings Plan (RRSP), a Deferred Profit Sharing Plan (DPSP), paid time off, and additional resources to support health and well-being.

Responsibilities

Day-to-day, this role blends data analysis, pipeline development, and cross-team collaboration. You’ll be expected to independently identify opportunities, build scalable solutions, and communicate findings clearly — all in service of improving the Alexa customer experience.

• Analyse complex datasets to identify patterns, understand root causes of anomalies, and inform product decisions
• Develop analysis and modelling approaches that drive product and engineering actions, directly improving the customer experience
• Build data pipelines and identify novel data sources from within Alexa and across Amazon to support analytical work
• Acquire and transform data using SQL and ETL queries to support research and reporting needs
• Partner with product stakeholders to translate causal insights into actionable recommendations
• Create data visualisations, presentations, and dashboards to drive awareness and adoption of data assets and product insights
• Mentor teammates and contribute to a culture of continuous learning and development
• Mechanise solutions into scalable and automated frameworks in collaboration with cross-disciplinary teams

Requirements / Skills

The ideal candidate brings a strong foundation in quantitative analysis and hands-on experience working with large, complex datasets in a fast-moving internet environment. Amazon values both technical depth and the ability to communicate findings clearly to a wide range of audiences.

• 1+ years of experience with data querying languages (SQL), scripting languages (Python), or statistical/mathematical software (R, SAS, Matlab, etc.)
• 2+ years of experience as a data/research scientist, statistician, or quantitative analyst at an internet-based company working with complex, big data sources
• 1+ years of experience contributing to mathematical textbooks, research papers, or educational content
• Master’s degree in STEM (Science, Technology, Engineering, or Mathematics) or equivalent practical experience
• Strong communication skills — ability to convey complex ideas clearly to both technical and non-technical audiences
• Preferred: Ph.D. in STEM, experience with ML concepts, clustered data processing (Hadoop, Spark, Hive), AI systems evaluation, and business intelligence tools (SPSS, SAS, R)

How to Apply

To apply, visit the official job posting using the link below. Make sure your resume is up to date and tailored to reflect your data science experience before submitting.

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