Senior Finance Data Scientist, Existing Business

Job Description

Intercom is the AI Customer Service company on a mission to help businesses provide incredible customer experiences. Our AI agent Fin, the most advanced customer service AI agent on the market, lets businesses deliver always-on, impeccable customer service and ultimately transform their customer experiences for the better. Fin can also be combined with our Helpdesk to become a complete solution called the Intercom Customer Service Suite, which provides AI enhanced support for the more complex or high touch queries that require a human agent. Founded in 2011 and trusted by nearly 30,000 global businesses, Intercom is setting the new standard for customer service. Driven by our core values, we push boundaries, build with speed and intensity, and consistently deliver incredible value to our customers. What's the opportunity? As a Senior Finance Data Scientist, Existing Business , you will be the architect of the systems that predict Intercom’s revenue future. You will move beyond static reporting to build production-grade forecasting models that translate complex customer behaviors into financial signals. You will work on high-impact, open-ended problems, such as predicting expansion propensity and modeling long-term customer LTV. This role requires a hybrid of financial intuition and technical rigor: the ability to navigate raw data warehouses and the strategic mindset to explain the "why" behind the numbers to our leadership team. The Impact You Will Have Own and Evolve the Revenue Engine: Build and maintain predictive models for usage-based revenue, renewals, and expansion that outperform traditional linear forecasts. Unlock Predictive Insights: Develop propensity models to identify expansion opportunities and churn risks before they materialize in the ledger. Architect Finance Data: Design and maintain curated datasets that serve as the single source of truth. Model Customer Value: Define and iterate on our LTV frameworks, providing a clear linkage between product engagement and long-term financial outcomes. Drive Scalability: Build automated, code-based forecasting workflows that increase the speed, reliability, and granularity of our financial planning. What will I be doing? Predictive Modeling and Forecasting Systems Build and own probabilistic and time-series models that project ARR performance across renewals and usage-based motions. Incorporate behavioral signals, such as product adoption, seat utilization, and feature engagement, into expansion propensity and LTV frameworks . Design models that account for cohort dynamics, seasonality, and product-led growth (PLG) signals. Evaluate

Required Skills