Senior Data Analyst

Trust & Will is a digital estate planning platform that provides accessible, legally valid wills, trusts, and estate settlement solutions. The Senior Data Analyst will own the end-to-end analytical engine, building data models, ensuring data reliability, analyzing conversion, retention, and lifetime value, and translating findings into business decisions. The role partners with marketing, engineering, finance, and executive leadership while mentoring analysts and supporting strategic roadmaps.

Responsibilities:

• Own the development of our data models within the lakehouse architecture; prioritize high-performance SQL, comprehensive documentation, and robust testing protocols
• Serve as a first line of defense for data reliability, proactively identifying and resolving upstream quality issues before they impact executive dashboards
• Architect the semantic layer and analytical structures that enable seamless self-serve exploration via AI and traditional BI platforms
• Serve as the primary data partner for marketing and engineering leadership, owning the analytical workstreams that support quarterly roadmap decisions
• Prepare and deliver data-driven recommendations to senior stakeholders and the executive team punchline first, minimum viable backstory, clear ask
• Mentor junior analysts and product/eng on methodology, communication, and prioritization; help build team-wide analytical standards
• For example, manage the Marketing Monitor, a 13-week rolling performance report tracking Gross Sales, multi-channel revenue (D2C, Advisor, Partnership), and unit economics (CAC, ARPM, CVR) with automated alerting
• Scale and optimize the suite of recurring analytical dashboards utilized by cross-functional leadership for weekly strategic calibration
• Guarantee data reliability and pipeline freshness; proactively interpret anomalies within an alerting framework to distinguish between statistical noise and meaningful business shifts
• Serve as the primary analytics responder for the business fielding requests from Finance, Marketing, Ops, Member Success, Partnerships, and Product. No data request is too small, but you also know when to use AI (or not)
• Translate vague business questions into well-scoped analytical problems, execute them in Snowflake/SQL, and deliver findings with a clear recommendation
• Proactively surface insights from data monitoring flag anomalies, trends, or risks before stakeholders ask
• Own ticket resolution quality: well-documented queries, auditable logic, and results stakeholders can act on

Requirements:

• You are a clear, concise communicator who can translate a complex regression or other mathematical reasoning into a one-paragraph recommendation for a non-technical stakeholder
• You are a data engineering and analyst hybrid  equally comfortable building a data model  and presenting the business implication to a Manager
• You have startup experience and know what it means to stand up an analytics function, ship scrappy analyses, and build toward rigor not wait for it
• You treat experimentation as a discipline, not a buzzword. You design tests, size samples, interpret results correctly, and know when an A/B test isn't the right tool
• You think in systems you connect your pipelines to business outcomes and are never satisfied stopping at the metric without asking why
• You operate with high autonomy and you identify the most important question, define the tim approach, execute the analysis, and deliver the recommendation without a detailed playbook
• You consider yourself AI-native and actively engage AI tools to accelerate your analytical, and data workflows, automate repetitive queries, and surface insights faster
• 5-9+ years of experience in analytics/data science and some data engineering or a closely related quantitative role
• Prior experience in a high-growth startup environment  you've operated with limited resources, ambiguous data, and shifting priorities and delivered anyway
• Demonstrated data background: you've built data models, designed and analyzed poor data pipelines and know what good is
• Experience owning a data domain end-to-end  not just answering requests, but generating the questions and driving decisions
• This position is available to candidates residing in the following states only: California (CA), Colorado (CO), Florida (FL), Georgia (GA), Idaho (ID), Illinois (IL), Maryland (MD), New Jersey (NJ), New York (NY), North Carolina (NC), Pennsylvania (PA), Texas (TX), Vermont (VT), Nevada (NV), Utah (UT)
• SQL: Advanced window functions, CTEs, complex joins, query optimization on large datasets
• Python: Proficient pandas/polars, statsmodels, scikit-learn, matplotlib/seaborn; you write clean, reproducible code
• BI / Visualization: ThoughtSpot, Omni, or equivalent, building dashboards that enable self-serve, not just answering one-off requests
• Data Modeling: Familiarity with dbt and the analytical data modeling - like ActivitySchema, Star Schema, etc
• Experience in fintech, legaltech, insurtech, or another regulated consumer vertical
• Experience with product-led growth (PLG) motions or B2B2C business models
• Contributions to building an analytics function from scratch, including metrics frameworks, data dictionaries, and experimentation standards
• Comfort working with an AI Data Analyst tool in a self-serve analytics context