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IREN

Operates renewable-powered AI GPU cloud infrastructure

Data Scientist - Full Stack

Data EngineeringConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA$190k - $240k /yr

About the Job

Requirements

  • A bachelor's degree in Computer Science, Engineering, Information Systems, Supply Chain, or a related field, or equivalent practical experience.
  • At least 5 years of experience in data engineering or data science, including at least 1 year building pipelines and data models for supply chain, procurement, operations, or finance data.
  • Strong data-driven storytelling skills and the ability to present findings clearly to technical and business audiences.
  • Working understanding of supply chain processes and stakeholder interactions, and experience working with ERP/MRP, CLM, PLM, or QMS tools.
  • Strong SQL and Python skills, and familiarity with dbt or an equivalent transformation framework.
  • Hands-on experience with a modern cloud data platform such as Snowflake, Databricks, BigQuery, or Redshift, and an orchestration tool such as Airflow, Dagster, Prefect, or similar.
  • Exposure to AI-native analytics tools and workflows.
  • Experience working with data from ERP and procurement systems, such as SAP, Oracle, NetSuite, Dynamics, Coupa, or Ariba, via APIs, extracts, or CDC.
  • Working knowledge of dimensional modeling, master-data concepts, and data-quality practices.
  • Software engineering fundamentals, including Git, code review, automated testing, and CI/CD basics.
  • Strong hands-on problem solving, data analysis, and communication skills, with the ability to work autonomously across analytics, engineering, and supply chain teams.
  • Must reliably commute to the assigned office on scheduled in-office days under the hybrid arrangement.
  • Willingness to travel domestically and internationally to supplier and vendor sites, data centers, implementation partner locations, and industry events.
  • Pre-employment screening, including background check and substance testing, may be required according to company policies.

Responsibilities

  • Design, build, and maintain reliable ELT/ETL pipelines from supply chain source systems, including ERP, procurement/P2P, inventory and warehouse, project controls, logistics, and supplier portals, into the analytics platform.
  • Integrate external data such as supplier catalogs, lead-time and market-price feeds, freight and customs data, and OEM shipment notifications.
  • Operate and improve pipeline orchestration, scheduling, monitoring, and alerting so data arrives on time and failures are detected before users see them.
  • Build and document the supply chain data model, including supplier, material/part, purchase order, contract, receipt, inventory, shipment, and project/site dimensions and facts.
  • Help define conformed dimensions and master-data rules, including supplier hierarchy, category taxonomy, and site and project codes, under the guidance of the Director, Supply Chain Analytics & Engineering and master-data owners.
  • Follow and help refine team engineering standards for version control, code review, testing, environments, and deployment.
  • Implement automated data-quality checks for completeness, freshness, and reconciliation to source, and publish data-quality metrics.
  • Maintain data lineage, definitions, and a catalog so analysts and business users can trust and find the data.
  • Implement the defined security model and privacy safeguards, address data-quality issues, and contribute to governance processes within allocated areas of ownership.
  • Partner with analysts to deliver datasets for spend cubes, supplier scorecards, lead-time and on-time-delivery tracking, inventory health, and transformation KPIs.
  • Design, build, and launch dashboards and visualizations supporting multiple use cases across different domains.
  • Contribute data foundations for forecasting and planning use cases such as demand and lead-time forecasting, should-cost, and supplier risk, and support analytics and data science teammates in productionizing models.
  • Support system-selection and implementation work for procurement, planning, and supplier-management tools by defining data requirements and integration patterns.

Desired Qualifications

  • Experience in data center, AI infrastructure, energy, construction, or other capital-project-heavy industries involving long-lead equipment such as GPUs, networking, transformers, switchgear, or generators.

About the Company

IREN

Operates renewable-powered AI GPU cloud infrastructure

IREN runs renewable-powered AI cloud and digital infrastructure by operating data centers and GPU clusters. Customers access high-performance NVIDIA GPUs and AI training/inference infrastructure through cloud-based services powered by grid-connected and renewable energy assets. It differentiates itself through full vertical integration of energy assets with compute infrastructure and a focus on North America. The company aims to provide scalable, renewable-powered AI compute for enterprises and developers to support large-scale AI workloads.

Company size
501-1,000
Company stage
IPO
Headquarters
Sydney NSW, Australia
Founded
2018

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