IREN
Data Scientist, Full Stack
$190K–$240K
San Francisco, California · Hybrid · Full-time · Posted Oct 30, 2026
- Experience
- 5+ years in data engineering or data science; at least 1 year building pipelines and data models in the specified domains.
- Education
- Bachelor’s degree in Computer Science, Engineering, Information Systems, Supply Chain or a related field, or equivalent practical experience.
- Visa sponsorship
- Participates in E-Verify and provides the federal government with Form I-9 information to confirm authorization to work in the United States.
About the job
Builds and operates supply-chain data pipelines, models, and dashboards to support analytics and planning across IREN’s AI infrastructure operations.
What you'll do
- Design and maintain ELT/ETL integrations, orchestration, data models, and data-quality processes for supply-chain systems and external data.
- Build datasets and dashboards for spend, suppliers, delivery, inventory, and transformation metrics; support forecasting and productionizing models.
- Contribute to data standards, governance, documentation, and integrations for procurement, planning, and supplier-management tools.
What they ask for
- 5+ years in data engineering or data science, including at least 1 year building supply-chain, procurement, operations, or finance pipelines and data models.
- Strong SQL and Python; familiarity with dbt or an equivalent transformation framework.
- Hands-on experience with a modern cloud data platform and an orchestration tool.
- Bachelor’s degree in a related field, or equivalent practical experience.
Nice to have
- Experience in data center, AI infrastructure, energy, construction, or other capital-project-heavy industries.
- Exposure to AI-native analytics tools and workflows.
Pay
USD $190,000-$240,000/annum (base salary)
Tools
SQL, Python, dbt, Snowflake, Databricks, BigQuery, Redshift, Airflow
AI focus
Contributes data foundations for forecasting and planning use cases, including demand and lead-time forecasting, should-cost, and supplier risk; supports productionizing models and has exposure to AI-native analytics workflows.
Model-written summary · the original posting is authoritative