Senior Product Data Analyst

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🕒 February 20

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Versapay

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2006

🤝 B2B

💳 Fintech

☁️ SaaS

💰 $4M Post-IPO Debt on 2019-11

B2B • Fintech • SaaS

Versapay is a company offering a collaborative accounts receivable (AR) network designed for industry-leading AR automation and B2B payment solutions. The platform provides tools to automate AR tasks, manage cash applications, and facilitate B2B payments across channels, integrating with ERP systems like Microsoft Dynamics, NetSuite, and Sage Intacct. Versapay's solutions help teams collaborate effectively over the cloud, reducing manual processing and improving cash flow. The company focuses on simplifying the invoice-to-cash process using artificial intelligence, enhancing customer experience with easy-to-use portals, and offering comprehensive digital payment methods. Versapay also supports large-scale B2B transactions worldwide, promoting efficiency and environmental benefits through digital invoicing.

📋 Description

• Design and maintain robust, documented data models in Snowflake that serve as the "source of truth" for product health, moving the team toward higher standards of data observability and reduced tech debt. • Partner with Product leadership to execute against their roadmap, specifically providing the analytical backbone for International Receivables, Agentic AI workflows, and embedded lending initiatives. • Serve as the lead analytical advisor to the CPO and Product Managers, translating complex data into actionable narratives that influence product strategy and development prioritization. • Conduct deep-dive research into user journeys to identify friction points and opportunities to enhance product stickiness. • Move beyond descriptive BI to implement predictive models, ensuring our product intelligence remains industry-leading. • Design and analyze A/B tests and causal inference models to measure the impact of new features on key metrics like DSO reduction and customer adoption.

🎯 Requirements

• 5+ years of experience in a product data analytics role, specifically supporting Product Management or engineering teams. • Advanced SQL & Analytics Engineering: Expert-level ability to write complex, performant queries and a deep understanding of how to structure behavioral data for self-service analysis. • Technical Stack: Proficient in Python for data manipulation and Tableau for high-impact visualization. • Product Growth Literacy: Solid understanding of product-led growth (PLG) metrics, retention analysis, and user lifecycle modelling. • Statistical Foundation: Practical experience with regression analysis, hypothesis testing, and a strong desire to explore AI/ML opportunities in a product context.