Data Scientist: Turn Data into Everyday AI Solutions

Amazon Inc.; Vancouver; On-site; CAD 90,000 - 140,000; Full time

Benefits offered by this job

Health insurance (medical, dental, vis

RRSP

Deferred Profit Sharing Plan (DPSP)

Paid time off

Job summary

Amazon Inc. in Vancouver, Canada, is seeking a Data Scientist to join the Alexa Daily Essentials team.

You will work with complex data, develop statistical methodologies, and provide product insights to shape AI-driven solutions across timers, alarms, calendars, and news experiences. You will build scalable data frameworks, collaborate with Analytics and Applied Science colleagues, and communicate findings to technical and non-technical stakeholders, driving data-driven decisions and product

Qualifications

• 1+ years of data querying languages (SQL) or scripting (Python) experience.
• 2+ years in data/research/scientific roles with large data sources.
• 1+ years creating or contributing to mathematical textbooks, research papers, or educational content.

Responsibilities

• Analyze complex data 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.
• Build data pipelines and identify novel data sources to leverage in analytical work.
• Excel at communicating complex ideas to technical and non-technical audiences and visualize data insights.

Skills

SQL

Python

R

SAS

MATLAB

Statistics

Education

Master's degree in STEM

PhD (preferred)

Tools

Hadoop

Spark

MapReduce

Hive

SAS

SPSS

R

Job description

Amazon Inc. in Vancouver, Canada, is seeking a Data Scientist to join the Alexa Daily Essentials team.

You will work with complex data, develop statistical methodologies, and provide product insights to shape AI-driven solutions across timers, alarms, calendars, and news experiences. You will build scalable data frameworks, collaborate with Analytics and Applied Science colleagues, and communicate findings to technical and non-technical stakeholders, driving data-driven decisions and product