Data Scientist

- 2+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- 1+ years of working with or evaluating AI systems experience
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
- Experience applying theoretical models in an applied environment
- Knowledge of machine learning concepts and their application to reasoning and problem-solving
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company
- Experience working on multi-team, cross-disciplinary projects
- Experience applying quantitative analysis to solve business problems and making data-driven business decisions
- Experience effectively communicating complex concepts through written and verbal communication

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status.

CAN, BC, Vancouver - 109,100.00 - 182,200.00 CAD annually
Join our Amazon Private Brands Selection Guidance organization in building science and tech solutions at scale to delight our customers with products across our leading private brands such as Amazon Basics, Amazon Essentials, and by Amazon.

The Selection Guidance team applies Generative AI, Machine Learning, Statistics, and Economics solutions to drive our private brands product assortment, strategic business decisions, and product inputs such as title, price, merchandising and ordering. We are an interdisciplinary team of Scientists, Economists, Engineers, and Product Managers incubating and building day one solutions using novel technology, to solve some of the toughest business problems at Amazon.

As a Data Scientist you will investigate business problems using data, invent novel solutions and prototypes, and directly contribute to bringing your ideas to life through production implementation. Current research areas include named entity recognition, product substitutes, pricing optimization, agentic AI, and large language models. You will review and guide scientists across the team on their designs and implementations, and raise the team bar for science research and prototypes.

This is a unique, high visibility opportunity for someone who wants to develop ambitious science solutions and have direct business and customer impact.

Key job responsibilities
- Partner with business stakeholders to deeply understand APB business problems and frame ambiguous business problems as science problems and solutions.
- Perform data analysis and build data pipelines to drive business decisions.
- Invent novel science solutions, develop prototypes, and deploy production software to solve business problems.
- Review and guide science solutions across the team.
- Publish and socialize your and the team's research across Amazon and external avenues as appropriate
- Leverage industry best practices to establish repeatable applied science practices, principles & processes.