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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist, Analytics - **Company:** Crusoe's Inc - **Location:** San Francisco, CA, United States - **Salary:** $136,850.0 - $161,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Data Analysis, Big Data, BigQuery, Data Centers, Data Validation, Information Engineering, Data Infrastructure, Data Integration, Data Warehousing, Cursor, Database Queries, Python (Programming Language), Oracle (Applications), Power BI, Sage Accounting, SAP (Applications), Tableau (Software), GitHub Copilot, Claude Code, Data Lakes, Data Management, Looker Analytics - **Published:** October 30, 2026 - **Apply:** https://www.dice.com/job-detail/49d6f2d4-f516-45ac-9026-4428383dedee ## About the Role * Business Acumen: You understand why you are building something, not just what. You ask questions until the business context is clear and you can explain your work to non-technical stakeholders. * Technical Fluency: Possess strong SQL skills -- you will query BigQuery daily. Comfort working with large, complex datasets across multiple source systems. * Modern Data Stack Experience: Experience with a modern data stack (BigQuery, dbt, Airflow, or equivalents). * Reporting Expertise: Experience building and maintaining dashboards and reports for operational use. Familiarity with BI tools (e.g., Sigma, Looker, Power BI, Tableau). * Stakeholder Management: Proven experience working directly with business partners to gather requirements and deliver data products. You are credible in a room with construction project managers and equally comfortable reviewing a data model with an engineer. * Ownership: Track record of being the go-to person for "is this number right?" You take accountability for data accuracy and do not wait to be told when something is off. Bonus Points * Background in construction, manufacturing, supply chain, or other operationally complex industries. * Experience with ERP systems (SAP, Oracle, Sage Intacct, or similar) and the data that flows from them. * Familiarity with master data management concepts and cross-system entity resolution. * Experience working in a fast-growing company where processes are still being built. * Python for data analysis is a plus but not required. * Experience with AI-assisted coding tools (e.g., Claude Code, Cursor, GitHub Copilot) to accelerate analytical work. ## Description Join Crusoe as a Data Scientist, a dedicated hire on our central Data Science and Engineering team. This full-time position offers you the opportunity to own the data and analytics function for key parts of the business, starting with the Data Center Infrastructure Group (DIG) -- the arm of Crusoe that builds and operates data centers, spanning real estate, energy, construction, and parts lifecycle management. As part of a central team, you will also have the opportunity to partner with other groups across the company as needs arise. You will partner directly with business stakeholders, translate their needs into analytical work, and own the reporting and data quality that leadership depends on for high-stakes decisions. What You'll Be Working On: * Own Reporting & Dashboards: Build and maintain the weekly and monthly reports and dashboards that business leaders rely on for operational decision-making. You are the DRI for accuracy and timeliness. * Partner with Business Stakeholders: Work directly with leaders across construction, real estate, energy, procurement, and other functions to gather requirements and translate business questions into analytical deliverables. * Drive New Data Integrations: Work with data engineering to identify and onboard data from third-party enterprise systems (ERP, procurement, asset management, etc.) into the data lake, defining requirements and validating data quality as new sources come online. * Track Complex Projects: The infrastructure side of Crusoe runs large, multi-year construction projects with long lead times and many vendors. You will build and maintain tracking for project progress, cost burn-down, timelines, and financial performance. * Translate Business to Technical: Take business requirements and produce technical or techno-functional specifications that data engineers can execute on. Bridge the gap between what the business needs and how the data platform delivers it. * Support Master Data Management: As the company matures its MDM and ERP practices, you will help ensure master data (vendors, parts, projects, cost centers, sites) is consistent and accurate across systems. * Champion Data Quality: Identify gaps and inconsistencies in data, investigate root causes, and work with data engineers to implement fixes. When a number is wrong, you own the resolution.