Senior Finance Data Scientist

the opportunity? As a Senior Finance Data Scientist, Existing Business , you will be the architect of the systems that predict Fin'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 Fin 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? 3+ years 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. #LI-Hybrid Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world. In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. At Fin, we want to give people what they need to do the best work of their careers. Our benefits and programs are designed to support your health and wellbeing, your family, your time away from work, and your financial future. Offerings vary by location in line with local practices and requirements. Learn more about working at Fin and the benefits we offer at fin.ai/careers . Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction