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ElevenLabs is seeking a Finance Data Scientist to join its central Data team as the first dedicated analytics partner to the Finance function. This is a high-impact role at a $22B-valued, venture-backed AI company that has raised $781M and serves millions of users and thousands of businesses including Deutsche Telekom and Meta.
In this role, you will own finance-facing analysis including revenue and ARR reconciliation, cohort and retention economics, and pricing and packaging experiments. You'll partner closely with Analytics Engineering to build and maintain the certified finance KPI layer (ARR, billing, revenue), serving as the first line of defense to catch data quality issues before they propagate. You'll build forecasting and scenario models that FP&A uses directly in planning and board reporting. A key responsibility is translating ambiguous finance questions from FP&A, RevOps, and leadership into clear, reusable analysis that drives decision-making as the company scales toward IPO.
ElevenLabs operates with a high-velocity, impact-driven culture emphasizing rapid experimentation, lean autonomous teams, and minimal bureaucracy. The company is AI-first across all functions and prioritizes talent over location. You'll have access to professional development stipends, annual company offsites, and co-working support if needed.
The role is remote-first and can be executed from anywhere in Europe or the US East Coast, with the ability to operate in CET/ET timezones required. Offices are available in London, Warsaw, Dublin, or New York if preferred.
REQUIREMENTS:
- 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: ARR, billing, revenue recognition, cohort economics—ability to speak FP&A's language
- Rigour around data quality: reconcile by default and explain variances, not just report them
- Strong stakeholder management with Finance leadership and ability to push back on ambiguous asks
BONUS:
- 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 modern warehouse (BigQuery), partnering directly with analytics engineers
