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Trust & Will, founded in 2017, is the leading digital estate planning platform serving over one million users. The company provides attorney-approved, legally valid documents and seamless online solutions for wills, trusts, and legacy planning, partnering with financial advisors, attorneys, and institutions.
You will own the analytical engine driving Trust & Will's business decisions across marketing, revenue, conversion, retention, and lifetime value. This is a high-ownership, non-reporting role where you define the questions worth asking, build the models that answer them, and guide the roadmap based on data insights. You'll partner closely with the Director of Data Engineering, engineering leadership, and marketing, with direct access to senior stakeholders.
Key responsibilities include:
**Data Modeling & Integrity**: Develop data models within the lakehouse architecture with emphasis on high-performance SQL, documentation, and testing. Serve as a first line of defense for data reliability, proactively identifying upstream quality issues. Architect the semantic layer and analytical structures enabling self-serve exploration via AI and BI platforms.
**Stakeholder Partnership**: Act as the primary data partner for marketing and engineering leadership, owning analytical workstreams supporting quarterly roadmap decisions. Prepare and deliver data-driven recommendations to executives with clear, concise communication. Mentor junior analysts and build team-wide analytical standards.
**Daily Analytical Work**: Manage recurring dashboards like the Marketing Monitor (tracking Gross Sales, multi-channel revenue, unit economics with automated alerting). Scale and optimize dashboards used by cross-functional leadership for weekly strategic calibration. Guarantee data reliability and pipeline freshness with proactive anomaly interpretation.
**Ad Hoc Analytics**: Field requests from Finance, Marketing, Ops, Member Success, Partnerships, and Product. Translate vague business questions into well-scoped analytical problems and execute with judgment about when to leverage AI tools.
The role requires someone who is a clear communicator translating complex analysis into business recommendations, a data engineering and analyst hybrid comfortable building models and presenting implications, with startup experience standing up analytics functions. You treat experimentation as a discipline, think in systems connecting pipelines to outcomes, operate with high autonomy, and are AI-curious about accelerating workflows. Estate planning is analytically interesting: low-frequency, high-intent product with B2C direct and growing B2B2C advisor channels requiring deep analytical depth to understand segment activation, conversion, retention, and compounding levers.
