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
- Build and improve forecasting and planning models across APB
- Partner with business, science, and tech stakeholders
- Develop end‐to‐end pipelines (feature engineering through training and deployment) on SageMaker, S3, and Datanet
- Replace manual spreadsheet‐driven processes with reproducible code‐driven pipelines and dashboards
- Evaluate model accuracy across business segments
- Contribute to APB's science standards and assess the org's AI framework and experimentation rigor
- Communicate findings clearly to non‐technical partners
Basic Qualifications
- 1+ years of experience in data querying languages (e.g., SQL), scripting languages (e.g., Python) or statistical/mathematical software (e.g., R, SAS, Matlab)
- 2+ years of experience as a data/research scientist, statistician, or quantitative analyst in an internet‐based company with complex and big data sources
- 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM) or equivalent experience in STEM fields
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 processing (e.g., Hadoop, Spark, Map‐reduce, Hive)
- Experience working with or evaluating AI systems
- 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.
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.
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