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Versapay

The first Collaborative Accounts Receivable Network. Accomplish more, get paid faster, and deliver better experiences.

Senior Product Data Analyst

Data AnalystData AnalystOtherRemoteSeniorTeam 201-500Since 2006H1B No SponsorCompany SiteLinkedIn

Location

United States

Posted

101 days ago

Salary

$110K - $130K / year

Seniority

Senior

Bachelor Degree5 yrs expEnglishPythonSQLTableau

Job Description

Senior Product Data Analyst

Versapay

• 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.

Job 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.

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