JobgetherRemote · Canada
1h ago
AmazonPosted 1mo ago
L4
Data Scientist
Data Scientist at Amazon scores 84 out of 100 on AI centrality, which makes it a Level 4 role on this board.
AU, NSW, Sydneyfull-time
AI in this role
ai-agents
Key job responsibilities
- Build Predictive Models: Design, develop, and deploy machine learning models (e.g., time-series forecasting, regression, classification) to predict inbound volumes, leveraging signals from demand forecasts, vendor behaviour, and upstream planning systems unique to the Australian supply chain.
- Drive Root-Cause Analysis: Apply statistical methods and causal inference techniques to quantify defect attributions across plan-over-plan changes, actuals-over-plan variances, and forecast accuracy degradation, translating complex analytical findings into actionable insights for stakeholders.
- Enable Automated Intelligence: Leverage agentic workflows and LLM-based pipelines to build self-improving prediction systems for inbound volumes, automating feature engineering, model retraining, and anomaly detection to replace manual heuristics.
- Advance Experimentation: Design and execute A/B tests and counterfactual analyses to measure the impact of supply chain interventions (e.g., buying policy changes, capacity adjustments) on inbound volume outcomes, providing rigorous evidence for decision-making.
- Influence Strategy: Synthesise insights across product demand forecasting accuracy, inventory efficiency, and capacity planning to build data-driven narratives that influence inbound volume projections and supply chain strategy at the leadership level.
About the team
Have you ever ordered a product on Amazon and wondered how it got to you so fast? Wondered where it came from and how much it cost? If so, Amazon's Supply Chain Optimisation Technology (SCOT) organisation is for you. At SCOT, we solve deep technical problems and build innovative solutions in a fast-paced environment. Learn more about SCOT: http://bit.ly/amazon-scot.
Basic qualifications
- 2+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
- 2+ years of data querying languages (e.g. SQL, Hadoop/Hive) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Master's degree in a quantitative field, or Bachelor's degree and 5+ years of a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science experience
- Experience applying theoretical models in an applied environment
Preferred qualifications
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company
Acknowledgement of country:
In the spirit of reconciliation Amazon acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community. We pay our respect to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.
IDE statement:
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.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
AI Agents
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: AI Agents. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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