4 months ago
Base Salary
$150k - $259k/yr
Responsibilities
- Work with operations, finance, and engineering to develop foundational data pipelines that provide single-source-of-truth accuracy.
- Improve ongoing data pipelines and simplify self-service support for business stakeholders.
- Perform system audits and create data-quality tests to ensure complete and accurate reporting.
- Develop scalable data models, analytical solutions, pipelines, and underlying tables.
- Build and maintain data warehouse, data mart, and business-intelligence reporting environments.
- Help users transition their workflows to the new data systems.
- Perform ad-hoc analyses and create core data models and pipelines to support decision-making and data exploration.
- Maintain an active Secret security clearance; Top Secret is preferred.
Requirements
- 5+ years of relevant work experience applying data modeling and analytical skills.
- Ability to create extensible, scalable data schemas and pipelines for downstream analysis.
- Mastery of SQL and relational databases.
- Experience with programming languages such as Python or R.
- Experience building reliable transformation layers and pipelines from ambiguous business processes.
- Experience with dbt for creating a foundation for data insights.
- Active Secret security clearance required; Top Secret preferred.
Benefits
- Base salary, equity, and benefits are available for eligible full-time roles.
- Comprehensive health, dental, and vision coverage.
- Retirement benefits, learning and development stipend, and generous paid time off.
- Some roles may be eligible for a commuter stipend.
- The listed Washington, DC base salary range is $150,400-$259,000 USD.
- Candidates must wait 90 days before being reconsidered for the same role.
About Scale AI
Scale AI builds data annotation services and AI development tools for enterprises and government agencies, sold as a platform and managed services. Its products include the Scale Generative AI Platform for building and evaluating agents and the Data Engine for collecting, curating, and labeling training data, including RLHF and model evaluation. Founded in 2016 and headquartered in San Francisco, the company is privately held and works across domains from computer vision to LLM applications.