Applied Scientist, Private Brands Discovery
Amazon · Vancouver, Canada · Applied Science
About this role
Amazon is hiring a mid-level Applied Scientist in the machine learning function based in Vancouver, Canada. The posting calls out experience with Python, Java, NLP, Deep Learning and roughly 3+ years of relevant work. Listed education preference: a master's degree or equivalent. Compensation is listed at C$149,300–C$249,300 per year.
- Role
- Applied Scientist
- Function
- machine learning
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Vancouver, Canada
- Experience
- 3+ years
- Education
- Master's degree
- Department
- Applied Science
- Posted
- Jan 8, 2026
More roles at Amazon
Job description
from Amazon careersThe Private Brands Discovery team designs innovative machine learning solutions to drive customer awareness for Amazon’s own brands and help customers discover products they love. Private Brands Discovery is an interdisciplinary team of Scientists and Engineers, who incubate and build disruptive solutions using cutting-edge technology to solve some of the toughest science problems at Amazon. To this end, the team employs methods from Natural Language Processing, Deep learning, multi-armed bandits and reinforcement learning, Bayesian Optimization, causal and statistical inference, and econometrics to drive discovery across the customer journey. Our solutions are crucial for the success of Amazon’s own brands and serve as a beacon for discovery solutions across Amazon. This is a high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and engineers. As a scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You…