Sr. Data Analyst

Bizee•Houston, TX

18h•Remote

About The Position

Bizee (formerly Incfile) has helped over 1 million entrepreneurs start and run their businesses. We are transforming from a transaction-focused formation business to an AI-powered operating system for entrepreneurs. We champion the everyday entrepreneur. We believe in self-determination, grit, and earned success. No fluff, no jargon, no pretense. We work hard, ship fast, and let our products speak for themselves. As a Data Analyst at Bizee, you will be the analytical partner to Product, Finance, Operations, and Growth teams. You will transform raw data into insights that drive business decisions: understanding customer behavior, measuring product performance, tracking unit economics, analyzing jurisdictional patterns, and identifying opportunities for growth. This is a business-facing analytics role with two unique dimensions. First, you will build Customer Intelligence: understanding who our customers are, how they behave, and what drives retention. Second, you will build Jurisdictional Intelligence: analyzing patterns across 50+ states to optimize pricing, identify compliance risks, and inform product strategy. This is an AI-augmented analytics role. You use Claude to write SQL faster, explore data, and generate initial dashboard designs. AI makes you more productive, not less valuable. We expect you to embrace these tools.

Requirements

Analytics Experience: 2-5+ years in data analytics, business intelligence, or similar roles. You have delivered insights that changed business decisions.
SQL Proficiency: You are comfortable writing complex queries: joins, window functions, CTEs, and subqueries. SQL is your primary tool.
BI Tools: Experience with Looker, Tableau, Power BI, Metabase, or similar. You can build dashboards that people actually use.
Customer Analytics: Experience with segmentation, cohort analysis, customer health scoring, or similar customer intelligence work.
Business Acumen: You understand business context: revenue models, unit economics, funnel metrics, and customer lifecycle.
Communication Skills: You can explain complex analysis to non-technical stakeholders. You tell stories with data.
AI Tool Adoption: You use (or are eager to use) Claude or similar AI tools to accelerate analysis and SQL writing.

Nice To Haves

You have built customer intelligence platforms: segmentation, health scores, or inputs for personalization systems.
Experience analyzing multi-state or multi-jurisdiction data (compliance, legal, regulatory, or tax).
You have used Claude or similar AI tools to accelerate your analytics workflow.
Experience with subscription/SaaS metrics: MRR, churn, LTV, CAC, cohort analysis.
Python or R skills for statistical analysis beyond SQL.
Background in fintech, legal tech, or SMB-focused businesses.

Responsibilities

Customer Intelligence: Segmentation models, customer health scores, lifecycle analysis, and churn prediction inputs powering AI recommendations.
Jurisdictional Intelligence: State-by-state performance analysis, fee structure optimization, compliance pattern identification, and market opportunity mapping.
Executive Dashboards: Build and maintain dashboards tracking company KPIs: revenue, conversion, retention, and unit economics.
Product Analytics: Funnel analysis, feature adoption tracking, and A/B test analysis supporting product decisions.
Financial Reporting: Partner with Finance on revenue recognition, cohort LTV analysis, and monthly business reviews.
Self-Service Analytics: Build data models and documentation that enable stakeholders to answer their own questions.
Customer Intelligence: Customer segmentation, behavior analysis, lifecycle tracking, and inputs for AI personalization and recommendations.
Jurisdictional Intelligence: State-level analytics, compliance patterns, fee analysis, and geographic performance tracking across 50+ jurisdictions.
Business Intelligence: Dashboards, reports, and visualizations that leadership uses to run the business.
Metric Definitions: Partner with stakeholders to define, document, and maintain consistent KPI definitions.
Stakeholder Partnerships: Be the go-to analytics partner for Finance, Product, Marketing, or Operations (depending on focus).
Data Storytelling: Turn complex analysis into clear narratives that drive action.