Make your impact within a rapidly growing Fintech Company

You will be the analytics owner for BILL's payments products within Payments and Financial Services (PFS), covering payment conversion and failures, card and pay-by-card, settlement, and monetization.

This is not a role that runs the analyses Product hands you. You will find what Product did not know to ask: the failure pattern quietly eroding conversion, the manual step that should be automated, the deep dive that changes a roadmap call. Your work is measured by the product and roadmap decisions it drives.

You will set the analytics agenda for payments, define the KPIs the business runs on, and build the production-grade data models behind them. You will partner directly with Product, Engineering, Product Marketing, Finance, and GTM leadership, with real ownership and executive visibility from day one.

Responsibilities

• Set the analytics agenda for Payments. Find product opportunities, data gaps, and automation candidates across payment methods, and bring them to Product as recommendations that shape the roadmap.
• Own the Payments analytics relationship. Define metrics and OKRs, run a standing review cadence with Product, and drive a deep-dive practice.
• Run experiments and apply causal inference, so recommendations rest on what moved a metric, not on correlation.
• Build and maintain production-grade data models in dbt with tests, documentation, and version-controlled workflows.
• Build with AI-assisted workflows by default, and automate recurring reporting to free your time for higher-value work.
• Drive executive reporting and its adoption across leadership and Product.
• Present with confidence to senior stakeholders, and hold your ground when a metric is contested.
• Partner with data engineering and finance to validate data quality and metric definitions, reconcile payment data against source systems, and fix documentation-to-logic drift when you find it.

We would love to chat if you have

• 5+ years in product analytics, data science, or a related quantitative field, owning a domain end to end.
• A track record of self-directed work: finding high-impact problems and shipping the fix.
• Advanced SQL and strong Python.
• Production experience with dbt or similar: models, tests, documentation, version-controlled review.
• Fluency in experimentation and causal inference, and the judgment to know when an experiment is the right tool.
• Genuine AI-native fluency. You already build with agentic coding tools, and you know from experience where their output can and cannot be trusted.
• The judgment to turn an ambiguous question into a metrics framework, and the spine to defend it.
• Data storytelling that turns a complex finding into a decision a product team acts on.
• Nice to have: experience with payments, fintech, or marketplace data, such as payment rails, settlement and reconciliation, fraud and risk signals, or pricing and monetization.

Visa Sponsorship

Responsibilities

• Set the analytics agenda for Payments. Find product opportunities, data gaps, and automation candidates across payment methods, and bring them to Product as recommendations that shape the roadmap.
• Own the Payments analytics relationship. Define metrics and OKRs, run a standing review cadence with Product, and drive a deep-dive practice.
• Run experiments and apply causal inference, so recommendations rest on what moved a metric, not on correlation.
• Build and maintain production-grade data models in dbt with tests, documentation, and version-controlled workflows.
• Build with AI-assisted workflows by default, and automate recurring reporting to free your time for higher-value work.
• Drive executive reporting and its adoption across leadership and Product.
• Present with confidence to senior stakeholders, and hold your ground when a metric is contested.
• Partner with data engineering and finance to validate data quality and metric definitions, reconcile payment data against source systems, and fix documentation-to-logic drift when you find it.

We would love to chat if you have

• 5+ years in product analytics, data science, or a related quantitative field, owning a domain end to end.
• A track record of self-directed work: finding high-impact problems and shipping the fix.
• Advanced SQL and strong Python.
• Production experience with dbt or similar: models, tests, documentation, version-controlled review.
• Fluency in experimentation and causal inference, and the judgment to know when an experiment is the right tool.
• Genuine AI-native fluency. You already build with agentic coding tools, and you know from experience where their output can and cannot be trusted.
• The judgment to turn an ambiguous question into a metrics framework, and the spine to defend it.
• Data storytelling that turns a complex finding into a decision a product team acts on.
• Nice to have: experience with payments, fintech, or marketplace data, such as payment rails, settlement and reconciliation, fraud and risk signals, or pricing and monetization.

Visa Sponsorship

Please note that this position is not eligible for visa sponsorship. Applicants must have authorization to work in the United States without requiring visa sponsorship now or in the future.

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