Director, Data Analytics
On-siteNew York City, New York, United States or New York, United States
Job Summary
Lead, hire, and develop a team of embedded analysts and data scientists across growth, product, markets, finance, risk, and institutional. Own the analytical standard, including rigor, decision-readiness, and honest assumptions, while partnering with business leaders to set each function's agenda. Protect the embedded model by ensuring analysts own outcomes rather than staffing a ticket queue. Build shared craft through review practices and experimentation standards, and partner with data platform leadership to graduate recurring analyses into modeled datasets. Own company-level reporting and board/investor numbers, develop analysts into senior individual contributors, and manage performance with transparency. This hands-on leadership role requires 10+ years in analytics or data science, including 4+ years managing analysts or scientists.
Required Qualifications
- 10+ years in analytics or data science
- 4+ years managing analysts or scientists
- Expert SQL
- Statistical grounding to review an experiment design or a causal claim and catch what is wrong with it
- Experience running an embedded or matrixed analytics team
- A clear point of view on where that model breaks down
- Credibility with senior business stakeholders
- A track record of developing analysts, including promoting people and managing others out when it was the right call
- Strong prioritization instincts across functions with genuinely competing demands and no obvious tiebreaker
- A hiring track record — you have built a team, not only inherited one
- Comfortable operating in a fast-moving environment where business logic changes frequently and you need to keep pace
Desired Qualifications
- Data science depth — experimentation design, causal inference, or predictive modeling
- Experience in a marketplace, exchange, or trading business where analytics sits close to the economics
- Experience in fintech, crypto, prediction markets, or other data-intensive financial products
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