Data Analyst

Staff Data Analyst

Join BILL as a Staff Data Analyst and help shape the future of AI-native financial management for small and midsize businesses. You will partner closely with the team building BILL.AI, our platform's AI program and shared foundation, working alongside product, engineering, and design leaders to define what success looks like as we transform BILL from a "do-it-with-me" tool into a "do-it-for-you" platform.

This role sits at the intersection of a genuinely new product domain and a cross-functional analytics challenge. You will be defining metrics for AI-powered workflows that do not have established benchmarks, measuring accuracy and trust in a domain where both are critical, and helping teams across Payments, Growth, and AP Product align around a shared understanding of how AI is performing across the BILL platform.

The right candidate brings the rigor of a seasoned analyst, the technical depth to build AI-powered analytics systems, and the curiosity of someone energized by ambiguity and first-principles thinking.

• Partner with product and engineering leaders across the AI program to define and own the metrics framework for BILL.AI, establishing the KPIs that matter: automation rates, no-touch workflow completion, AI accuracy, customer trust signals, and engagement across interaction channels including in-product, SMS, and Slack.
• Conduct deep-dive analyses that go beyond surface-level dashboards, decomposing the drivers behind AI adoption and drop-off, identifying where the platform is building customer trust and where it is losing it, and surfacing findings that directly inform roadmap prioritization.
• Build AI-augmented analytics systems that scale insight generation across the program, including LLM-powered tooling for synthesizing qualitative signals, automating insight extraction, and surfacing patterns that traditional analytics methods cannot efficiently capture at volume.
• Serve as the analytical connective tissue across the AI program, working cross-functionally with teams spanning Integrated Experiences, APARAC Product, Payments, and Growth to ensure consistent metric definitions, avoid duplicated instrumentation, and enable reliable self-serve analytics.
• Design and analyze experiments in new territory, building frameworks that allow teams to run rigorous tests even where there is no historical precedent, including studies of automation acceptance, AI transparency, and interaction model preferences.
• Build scalable, reusable analytics infrastructure including dbt models, dashboards, and standardized metric definitions that serve multiple teams and reduce duplicated work across the analytics organization.
• Translate complex AI performance signals into clear narratives and recommendations for Director and VP-level stakeholders, influencing decisions with data and defending analytical conclusions with confidence.
• Mentor and develop junior and mid-level analysts on the team, providing technical feedback, guidance on problem-scoping, and support in navigating a complex cross-functional program environment.

• 5 or more years of experience in a data analyst role within a technology-driven or fintech environment.
• A demonstrated track record of building metrics frameworks from the ground up in ambiguous, fast-moving product areas.
• Advanced proficiency in SQL, and familiarity with Python for analysis
• Experience with dbt and data modeling, including designing reusable, production-grade data assets consumed by multiple teams.
• Experience building or integrating with LLM APIs (such as OpenAI, Gemini, or Anthropic) to create scalable, AI-powered analytics workflows.
• Strong experience with A/B testing and experiment design, including comfort operating in domains where controlled experimentation is limited.
• Excellent data quality instincts, with experience identifying inconsistencies at the source rather than only in downstream reporting.
• Strong written and verbal communication skills, with the ability to present analytical findings and recommendations to senior leadership with clarity and confidence.
• A degree in a quantitative field such as Statistics, Data Science, Mathematics, Economics, or Computer Science.

• Experience applying NLP or LLM-based techniques to analyze qualitative data at scale, such as customer feedback, transcripts, or survey responses.
• Background in financial operations, fintech, or payments data domains.
• Experience in a cross-functional analytics role where influence extended beyond a single feature team or reporting structure.
• Familiarity with AI workflow automation tooling such as n8n or similar platforms.