Head of Data, Analytics, & Intelligence

Bizee•Houston, TX

About The Position

Bizee (formerly Incfile) has helped over 1 million entrepreneurs start and run their businesses. We're 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. We're looking for the Head of Data, Analytics & Intelligence who share these values and want to build the Data, Analytics and Insights backbone that powers the next generation of American businesses. What Makes Working Here Different AI-Native Data Leadership: AI isn't a bolt-on; it's our core. You'll build the data foundation that powers predictive systems, personalization, and intelligent automation. High Agency, High Impact: You own the enterprise data strategy. We don't do "dashboard requests" from the top down; you identify the data capabilities that drive business transformation. Greenfield Opportunity: We're building our data platform from the ground up. You'll define the architecture for how data flows, how insights are delivered, and how AI systems are enabled. 2028 Strategic Transaction: We have a clear timeline and goals. Your success in building trusted data infrastructure and demonstrating business intelligence maturity directly drives company valuation. The Role As the Head of Data, Analytics & Intelligence, you own the intelligence foundation of the Bizee OS. You will design and deliver the enterprise data platform that powers Bizee's transformation from a transaction-based business formation company to a subscription-driven entrepreneur services platform. We are looking for business-minded data leader who understands that data strategy serves business model evolution. You will create the Master Data Repository leading the transformation of Bizee Data from a transactional to subscription platform. You will partner deeply with Marketing on acquisition efficiency, with Product on customer intelligence and Finance on unit economics, with. You'll influence the executive team on how data becomes a strategic asset. Reports to CTO.

Requirements

Data Leadership Experience: 10+ years spanning strategy, architecture, and analytics with demonstrated experience transforming data capabilities at a growth-stage company ($50M-$500M revenue).
Marketing Analytics Depth: Deep expertise in MMM, attribution modeling, and CAC/LTV analysis. You understand how to measure marketing effectiveness, not just report on it.
Finance Partnership: Strong experience with unit economics, cohort analysis, and revenue forecasting. You've been the trusted data partner to a CFO.
Technical Fluency: You can hold your own in a room of architects. You understand modern data stack: warehousing, ETL/ELT, BI tools, and data governance platforms.
Distributed Systems Experience: You've managed data synchronization across ERP (NetSuite preferred), CMS, and transactional systems. You know the pain of reconciliation.
Team Builder: Track record of building and leading high-performing analytics teams.
Business Outcome Orientation: You measure success by decisions enabled and revenue impact, not dashboards shipped.

Nice To Haves

You've led a successful Master Data Management (MDM) implementation that actually stuck.
You have a strong opinion on how data strategy enables business model transformation (transaction to subscription).
You can demonstrate how you've used AI tools (Claude, ChatGPT, etc.) to accelerate data analysis and insight generation.
You've worked in compliance-heavy or regulated industries requiring jurisdictional data management.
You've worked in the "Prosumer" or SMB space and understand the unique data challenges of serving small business owners at scale.

Responsibilities

Enterprise Data Architecture: Document and begin executing a data strategy aligned to business model transformation (transaction to subscription).
Clean Data Room: Establish Master Data Records for core domains (Customer, Product, Jurisdiction, Transaction) with definitions, reconciliation, and governance.
Marketing Analytics Platform: Implement Marketing Mix Modeling (MMM), CAC dashboards by channel, and attribution system enabling Growth team to optimize spend.
Customer Data Platform: Build the data foundation that powers customer intelligence, product decisions, compliance automation, and AI/ML systems.
Finance Partnership: Deliver unit economics models, LTV:CAC analysis, cohort profitability, and subscription metrics integrated with financial planning.
Data Synchronization: Ensure reliable data flow across CMS, NetSuite, payment systems, and customer applications with clear ownership and SLAs.
Executive Dashboards: Business intelligence layer delivering decision-ready insights to leadership and board.
Lead Master Data Record (MDR) creation and Clean Data Room initiatives: definitions, reconciliation, alignment, and ongoing management
Design enterprise data architecture supporting business model evolution: transaction capture, subscription lifecycle, customer health, predictive upsell/cross-sell
Own data synchronization across distributed systems: CMS, NetSuite, payment processors, state filing systems, and customer-facing applications
Establish data governance, quality standards, and stewardship models that scale with the business
Build marketing analytics infrastructure: Marketing Mix Modeling (MMM), attribution systems, channel effectiveness measurement
Own Customer Acquisition Cost (CAC) analysis across channels, cohorts, and campaigns
Deliver actionable insights that inform spend allocation, campaign optimization, and growth strategy
Partner with Growth and Marketing to enable data-driven experimentation and performance measurement
Partner with Finance on unit economics modeling, LTV:CAC analysis, cohort profitability, and forecasting
Build executive and operational dashboards surfacing business health, trends, and decision-relevant metrics
Enable revenue recognition, subscription analytics, and financial reporting from clean, trusted data sources
Support board and investor reporting with reliable, auditable data
Build unified customer profiles powering personalization, recommendations, and lifecycle automation
Own the data layer for filing rules engine, compliance alerts, and jurisdiction-specific business logic
Deliver product analytics informing roadmap decisions, feature effectiveness, and customer behavior insights
Enable AI/ML systems with clean, well-structured training data and feature stores