# Senior Finance Data Scientist, Existing Business **Company**: Intercom **Location**: Dublin, Ireland **Work arrangement**: hybrid **Experience**: senior **Job type**: full-time **Category**: Finance **Industry**: Technology **Apply**: https://job-boards.greenhouse.io/intercom/jobs/7774230?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_7c9f7a0b-319 ## Description 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. ### Responsibilities - 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. - Data and Analytical Infrastructure: Own the end-to-end data pipeline for finance, transforming raw product usage and billing data into curated, model-ready datasets in our data warehouse. - Analytical Problem Solving: Translate ambiguous business questions into structured data science projects. - Business Partnership & Communication: Partner with Sales, Product, and Data Engineering to align our financial models with actual customer behavior and product roadmaps. ### What skills do I need? - 5 to 8 years of experience in Data Science, Strategic Finance, or Revenue Analytics, with a deep focus on SaaS or usage-based business models. - Advanced Technical Skills: High proficiency in Python (pandas, scikit-learn) and Expert-level SQL. Experience with forecasting libraries (e.g., Prophet, Nixtla) is a major plus. - System Design Mindset: Experience building scalable data pipelines and production-grade analytical tools, not just one-off spreadsheets. - SaaS Mastery: Strong understanding of NRR, LTV, Churn, and the relationship between product usage and revenue. - Communication: Ability to translate technical work into business insight and influence stakeholders through data-driven storytelling. - Business Judgment: A focus on accuracy and a "Product Sense" that allows you to see the human behavior behind the data points. - AI-Augmented Productivity: Proficiency in leveraging AI-native development tools (e.g. Cursor, Claude Code) to accelerate the development of data pipelines, model prototyping, and code documentation. ### What Success Looks Like - Automated forecasting models that are more accurate, granular, and less manual than previous iterations. - A clear Propensity Score integrated into our planning that successfully predicts customer expansion and contraction. - Scalable, code-based workflows that reduce the time-to-insight for the Existing Business team. - High confidence from leadership in our ability to predict the financial impact of changing customer usage patterns. ## Skills ### Required - Python - SQL - ούς - Forecasting - Data Science - Strategic Finance - Revenue Analytics - SaaS - NRR - LTV - Churn - Product Usage - Data-Driven Storytelling - AI-Augmented Productivity --- Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/intercom/jobs/7774230?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)