Data Scientist

Amazon; Australia; On-site; AUD 120,000 - 170,000; Full time

Job summary

Amazon is seeking a Data Scientist for the SCOT team in Australia to help build analytical foundations that automate and optimise the local supply chain at scale.

You will design predictive models, perform root-cause analyses, and contribute to self-improving pipelines while collaborating with cross-functional teams to drive data-driven decisions.

Qualifications

• 2+ years as data scientist or similar role with data extraction, analysis, statistics, and communication.
• 2+ years of data querying languages (e.g., SQL, Hadoop/Hive).
• 3+ years of ML/statistical modeling and data analysis techniques.
• Master's degree in a quantitative field, or Bachelor's + 5+ years in a quantitative field.
• Experience applying theoretical models in an applied environment.

Responsibilities

• Build predictive models to forecast inbound volumes using demand signals and planning systems.
• Drive root-cause analyses to quantify defect attributions across plan changes and forecast variances.
• Enable automated intelligence with ML pipelines, feature engineering, and anomaly detection.
• Design and run A/B tests and counterfactual analyses to measure interventions' impact on inbound volume.
• Synthesize insights to influence inbound projections and supply chain strategy.

Skills

SQL

Python

Machine learning

Statistical modeling

Education

Master's degree (quantitative field)

Bachelor's + 5+ years (quantitative field)

Tools

Hadoop/Hive

Job description

Job ID: 10509589 | Amazon Commercial Services Pty Ltd

Amazon's operations in Australia is at a unique phase of rapid expansion. As our selection and local fulfilment network grows, the complexity of managing supply chain increases. To systemically address these complexities, we are establishing a team of subject matter experts by expanding Supply Chain Optimisation Technology (SCOT) team presence to Australia. We are looking for an exceptional Data Scientist to join this specialised team and help build the analytical foundations that allow us to automate and optimise our local supply chain at scale.

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.

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