Senior Data Analyst

About You: 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 time 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.

About the Role: We're looking for a Senior Data Analyst to own the end to end analytical engine behind Trust & Will. This is a high-ownership role: you'll work across marketing, and revenue to understand what's driving conversion, retention, and lifetime value and you'll translate those findings into decisions that move the business. This is not a reporting role. You will define the questions worth asking, build the models that answer them, guide the roadmap based on what the data shows. You'll partner closely with the Director of Data Engineering, engineering, and marketing leadership and you'll have direct access to senior stakeholders. The core challenge is analytically interesting: estate planning is a low-frequency, high-intent product with a B2C direct channel and a growing B2B2C advisor network. Understanding how different user segments activate, convert, and retain and which levers compound requires real analytical depth. You'll have the data, the infrastructure, and the mandate to figure it out.

Data Modeling & Integrity: 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.

Stakeholder Partnership & Communication: 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. Daily Analytical WorkFor 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.

Ad Hoc Analytics: 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.

Qualifications: Core Experience 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 isExperience 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) Technical SkillsSQL: 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: Thought Spot, 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 Activity Schema, Star Schema, etc.

Bonus Points: 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.

Compensation: Salary + EquityOur salary range for this position is $140,000 - $180,000. In addition to compensation, we include an employee equity package as part of our offer, along with other benefits and perks outlined below. PTOFlexible time off that you are encouraged to use Generous paid company holidays and breaks throughout the year Monthly friends & family day Paid time off to volunteer in your community Health and Wellness Benefits Exceptional health benefits including medical, dental, vision, life, and disability insurance - we cover 100% of premiums for employees and dependents on medical coverage Mental health support through Spring Health, plus access to One Medical for primary care and Cleo for family planning and caregiving Financial wellness benefits (unlimited 1:1 sessions with a UBS financial coach and employer-sponsored 401k with up to 4% company match) Extra Flexible work schedule + hours Family-friendly work environment. We support the complexity of a remote world with the needs of families Up to $1,000 annually in learning & development reimbursement