Finance Data Scientist

Overview

Join the central Data team as the first dedicated analytics partner to Finance. Turn billing, revenue and forecasting data into audit-ready numbers and analysis that shapes pricing and planning decisions as the company scales towards IPO.

What you'll do

• Own finance-facing analysis, including revenue and ARR reconciliation, cohort and retention economics, and pricing and packaging experiments.
• Partner with Analytics Engineering on the certified finance KPI layer covering ARR, billing and revenue.
• Catch when a finance number is quietly wrong.
• Build forecasting and scenario models that FP&A uses directly in planning and board reporting.
• Translate ambiguous finance questions from FP&A, RevOps and leadership into clear, reusable analysis.

What you'll need

• Demonstrated experience as a data scientist or analyst embedded with a Finance / FP&A function, ideally at a growth-stage or pre-IPO company.
• Strong SQL and Python, with comfort reconciling data across Stripe, Salesforce and a dbt-modelled warehouse.
• Finance fluency in ARR, billing, revenue recognition and cohort economics, with the ability to speak FP&A's language.
• Rigour around data quality, including reconciling by default and explaining a variance, not just reporting it.
• Strong stakeholder management with Finance leadership and the ability to push back on ambiguous asks.

Nice to have

• Experience preparing finance data for audit, SOX or IPO readiness.
• Experience with pricing / packaging experimentation or revenue forecasting at a subscription or usage-based business.
• Experience with dbt or a modern warehouse such as BigQuery, partnering directly with analytics engineers.

Details

• The role is remote-first and can be executed from anywhere in Europe or the US East Coast.
• The role requires the ability to operate in CET / ET timezones.
• If preferred, the role can be performed from offices in London, Warsaw, Dublin or New York.