Crusoe
Senior Data Scientist, Research Engineer
San Francisco, CA - US. Posted 8 months ago
The role
This person will build and deploy forecasting and analysis models for financial and product decisions. They will also perform root cause analysis for operational incidents and analyze cloud infrastructure product usage.
What you will do
- Build and deploy models for financial forecasting and product analysis.
- Investigate operational incidents and predict failures.
- Implement solutions for system reliability and efficiency.
- Conduct deep analysis of cloud infrastructure product usage and performance.
- Collaborate with internal teams to maintain high-quality data.
- Contribute to the scalable evolution of modern data infrastructure.
Required qualifications
- Familiarity with Monte Carlo simulation, predictive analytics, and time series modeling.
- Proficiency in SQL and Python for data analysis.
- Strong understanding of current data infrastructure architectures.
- Familiarity with data visualization tools (e.g., Tableau, Power BI, Looker).
- Proven track record and passion for data quality.
- Ability to act autonomously to drive forward analytics projects.
Nice to have
- Advanced degree (Master's or Ph.D.) in a quantitative field (e.g., Data Science, Statistics, Computer Science) or equivalent experience.
- Experience building cloud infrastructure (e.g., AWS, GCP, Azure).
- Experience on a growing or early-stage data team, contributing to foundational development.
Benefits
- Competitive compensation
- Restricted Stock Units
- Paid time off & paid holidays
- Comprehensive health, dental & vision insurance
- Employer contributions to HSA account
- Paid parental leave
- Paid life insurance, short-term and long-term disability
- Professional development & tuition reimbursement
- Mental health & wellness support
- Commuter benefits (parking & transit)
- Cell phone stipend
- 401(k) Retirement plan with company match up to 4% of salary
About the company
Crusoe is a vertically integrated AI infrastructure company that owns and operates each layer of the stack to power AI workloads. They use an energy-first approach to meet the demand for AI compute.