Senior Finance Data Scientist, Existing Business

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 model performance through backtesting and iteration, ensuring our "financial weather forecast" is constantly improving.

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.
• Write and optimize production-quality SQL and Python to work with large-scale datasets and automate complex FP&A workflows.
• Ensure data integrity and consistency across all predictive systems and executive dashboards.
• Contribute to the long-term data strategy for how Intercom tracks and predicts Existing Business health.

Analytical Problem Solving

• Translate ambiguous business questions (e.g., "Which usage signals best predict a 2x expansion?") into structured data science projects.
• Connect ARR outcomes to underlying drivers like product adoption, customer health scores, and GTM activity.
• Perform scenario modeling and sensitivity analysis to help the business understand the range of possible outcomes for NRR.

Business Partnership & Communication

• Partner with Sales, Product, and Data Engineering to align our financial models with actual customer behavior and product roadmaps.
• Translate complex statistical outputs into clear, decision-oriented narratives for the CFO and executive leadership.
• Build executive-ready materials, including predictive dashboards and strategic presentations.

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.

Benefits 

We are a well-treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us! 

• Competitive salary and equity in a fast-growing start-up
• We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen
• Regular compensation reviews - we reward great work!
• Pension scheme & match up to 4%
• Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents
• Flexible paid time off policy
• Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones
• If you’re cycling, we’ve got you covered on the Cycle-to-Work Scheme. With secure bike storage too 
• MacBooks are our standard, but we also offer Windows for certain roles when needed.

#LI-Hybrid