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# Senior Data Scientist, Research Engineer

- **Company:** Crusoe's Inc
- **Location:** Sunnyvale, CA, United States
- **Experience:** Expert
- **Salary:** $166,000.0 - $200,000.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Microsoft Azure, Cloud Computing, Data Infrastructure, Data Visualization, Monte Carlo Methods, Power BI, SQL Databases, Tableau (Software), Google Cloud, Reliability of Systems, Build Management, Information Technology, Looker Analytics
- **Published:** October 27, 2026
- **Apply:** https://www.thejobnetwork.com/job/71706773-df57-4fcd-8236-048cba093bf8/senior-data-scientist-research-engineer

## About the Role

* Analytical Expertise: Demonstrate deep familiarity with core analytical methods including Monte Carlo simulation, predictive analytics, and time series modeling.
 * Technical Fluency: Possess proficiency in SQL and Python for data analysis, alongside a strong understanding of current data infrastructure architectures.
 * Data Visualization Proficiency: Familiarity with data visualization tools (e.g., Tableau, Power BI, Looker) to communicate insights effectively.
 * Commitment to Quality: Show a proven track record and passion for data quality.
 * Ownership: As an early hire on the data science team, you'll be expected to act autonomously to drive forward analytics projects.

Bonus Points (but not requirements):

 * 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.

## Description

* Develop Forecasting & Analysis Models: Build and deploy models for financial forecasting and product analysis to drive strategic decisions.
 * Perform Root Cause Analysis & Prediction: Investigate operational incidents and predict failures, implementing solutions for system reliability and efficiency.
 * Analyze Cloud Infrastructure Products: Conduct deep analysis of cloud infrastructure product usage and performance to identify areas for improvement and guide feature development.
 * Champion Data Quality & Infrastructure: Collaborate with internal teams on initiatives to maintain high-quality data and contribute to the scalable evolution of our modern data infrastructure.