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Intercom (Fin AI) is seeking a Senior Finance Data Scientist to architect predictive systems that forecast revenue and customer lifetime value. This role bridges financial strategy and advanced analytics, requiring both technical rigor and business acumen.
You will own the end-to-end development of probabilistic and time-series forecasting models that predict ARR performance across renewals and usage-based revenue motions. Key responsibilities include building expansion propensity and LTV frameworks that incorporate behavioral signals—product adoption, seat utilization, feature engagement—while accounting for cohort dynamics, seasonality, and product-led growth patterns. You will design and maintain curated, model-ready datasets in the data warehouse, writing production-grade SQL and Python to transform raw product usage and billing data into reliable analytical assets.
Beyond modeling, you will translate ambiguous business questions into structured data science projects, performing scenario modeling and sensitivity analysis to help leadership understand possible outcomes for net revenue retention. You will partner closely with Sales, Product, and Data Engineering teams to align financial models with actual customer behavior and product roadmaps, then communicate complex statistical findings as clear, decision-oriented narratives for the CFO and executive team.
The role demands 3+ years in Data Science, Strategic Finance, or Revenue Analytics with deep SaaS or usage-based business model experience. You should be proficient in advanced statistical modeling, SQL, Python, and data visualization tools. Experience with probabilistic forecasting, causal inference, or machine learning in financial contexts is valued. You will work in a hybrid arrangement in Dublin, collaborating with a global team at one of the world's largest private software companies.
