Amazon. com. ca, ULC

Data Science, Science, Retail

DataScientist,PrivateBrandAnalytics

CA$85–142k Vancouver, British Columbia, Canada FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“Data Scientist, Private Brand Analytics at Amazon. com. ca, ULC. Skills: Forecasting, Applied ML, Data pipelines. Build forecasting models. Improve forecasting models”

What You'll Achieve.

Improve business performance

Industry & Context.

Data Science, Science, Retail
Problems you'll solve

Problem-solving

What They're Looking For.

Must Have

1+ years data querying languages, 1+ years scripting languages, 1+ years statistical software, 2+ years data scientist experience, 1+ years creating educational content

Nice to Have

Knowledge of statistical packages, Knowledge of business intelligence tools, Knowledge of machine learning concepts, Experience with clustered data processing, Experience working with AI systems, Experience applying quantitative analysis, Effectively communicating complex concepts

What You'll Do.

Build forecasting models

Improve forecasting models

Develop end-to-end pipelines

Replace manual processes

Create reproducible pipelines

Build code-driven pipelines

Evaluate model accuracy

Assess experimentation rigor

How You'll Work.

Team & Collaboration

Business stakeholders; Science stakeholders; Tech stakeholders; Senior scientist

Communication Scope

Communicate findings

Full Job Description

This role is on the Core Tech Private Brands Analytics (PBA) team, a cross-functional team (software engineering, data science, data engineering, business intelligence) that owns Amazon Private Brands (APBs) central data infrastructure and builds platforms and models that help improve business performance. In this job you will build and improve forecasting and planning models across APB, partnering with business, science, and tech stakeholders. Day-to-day work includes end-to-end pipeline development (feature engineering through training and deployment) on SageMaker, S3, and Datanet, replacing manual spreadsheet-driven processes with reproducible code-driven pipelines and dashboards, evaluating model accuracy across business segments, and contributing to APB's science standards alongside a senior scientist assessing the org's AI framework and experimentation rigor. Key job responsibilities The ideal candidate has strong fundamentals in forecasting and applied ML, experience with Python and SQL, comfort working with large-scale retail datasets, and the ability to communicate findings clearly to non-technical partners. Basic Qualifications: - 1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience - 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience - 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience - Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM) Preferred Qualifications: - Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R - Knowledge of machine learning concepts and their application to reasoning and problem-solving - Experience with clustered data pr

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