Senior Director of Analytics & Data Science
- San Francisco, United States
- Director/Executive
- 15+ years
- Master's degree
- Posted
Skills
Required
- Data Science
- Analytics
- forecasting
- SQL
- Python
- data modeling
- BigQuery
- Airflow
Preferred
- capacity planning
- cloud or infrastructure business models
- ARR
- utilization
- AI-assisted coding
- Claude
- Code / Cursor / GitHub
- Copilot
- fleet management
Join Crusoe, a leading company in the AI and cloud services industry. As the Senior Director of Analytics & Data Science, you will lead a newly formed team of analysts and data scientists, driving data-driven decision-making across various business units. You will define the operating model, hire and develop the team, set standards for analytical rigor, and partner with leadership to make faster, better-informed decisions. This is a hands-on leadership role for someone who thrives in a fast-paced, dynamic environment.
Establish and lead a centralized team of analysts and data scientists, defining the operating model and staffing to meet the analytical needs of various business units.
Responsibilities
- Set standards for analytical rigor, overseeing statistical and modeling work, and ensuring the team approaches forecasting, experimentation, and predictive work effectively.
- Own certified reporting for the executive team, the board, and cross-business questions, driving high-stakes decision support through clear analysis and recommendations.
- Ownership: Track record of being the go-to person for "is this number right?" You find problems before they surface in an executive meeting and you own the resolution
- Comfort Building from Scratch: You are energized by unpaved paths, incomplete data, and processes that do not exist yet
- Executive Communication: Credibility in a room with the CFO and business unit leaders. You can defend a number, explain a method to a non-technical audience, and disagree with a stakeholder without damaging the relationship
- Business and Financial Acumen: Comfort with P&L mechanics, unit economics, capital projects, and returns analysis. You understand why you are building something, not just what, and you can connect an operational metric to a financial outcome
Requirements
- Analytics & Data Science Leadership: 15+ years in analytics or data science, with 5+ years leading teams that include data scientists as well as analysts and analytics engineers. You’ve hired for both disciplines and set technical standards across them
- Technical Depth: Fluency with SQL and Python, strong data modeling instincts, and hands-on experience with dbt or equivalent. You can build a certified data mart yourself and review your team’s models substantively
- Organizational Navigation: Proven ability to operate in a dotted-line structure with competing priorities, earn trust from leaders within the business units, and optimize for the whole company rather than any one team
- Governance Judgment: Experience defining and certifying metrics, testing business rules, resolving entities across systems, and holding the line on definitions when a stakeholder wants their own version of a number
- Data Science Depth: Direct experience applying forecasting, experimental design, and statistical inference to business problems, including ownership of models in production
- Modern Data Stack Experience: Experience with a modern data stack (BigQuery, dbt, Airflow, or equivalents)
- Advanced degree (Master's or Ph.D.) in a quantitative field (e.g., Data Science, Statistics, Computer Science) or equivalent experience
- Experience in capital-intensive or operationally complex industries: energy, construction, manufacturing, supply chain, or data center development
- Experience in a hypergrowth company where processes were still being built
Preferred
- Familiarity with cloud or infrastructure business models, including ARR, utilization, and capacity planning economics
- Hands-on use of AI-assisted coding tools such as Claude Code, Cursor, or GitHub Copilot to accelerate analytical work
- Experience applying forecasting or optimization to physical operations, e.g., capacity planning, supply chain, energy, or fleet management
- Experience enabling LLM or MCP-based self-service analytics on top of governed data models
Pay
USD 310,000 - 355,000
