F&S COE Analyst

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Role Overview We are seeking an analytically-driven Data Analyst to join our Finance Strategy team at Stripe. This role bridges the gap between data science and financial planning, requiring someone who can transform complex business data into actionable financial insights. You will build sophisticated dashboards, develop predictive models, and serve as the technical backbone for our FPA and GTM analytics initiatives. This is a unique opportunity for a data professional with financial acumen to directly influence strategic business decisions in a high-growth fintech environment. What You'll Do Financial Data Analytics Modeling Design, build, and maintain financial dashboards for FPA, Revenue Operations, and GTM teams using Tableau, Power BI, or Looker Develop automated financial reporting solutions that reduce manual effort and improve data accuracy Create sophisticated data models to support budgeting, forecasting, variance analysis, and scenario planning Build predictive models for revenue forecasting, customer lifetime value, churn analysis, and unit economics Business Intelligence Reporting Partner with Finance Business Partners and FPA teams to translate business requirements into technical solutions Design and implement data infrastructure for financial planning cycles (monthly/quarterly reviews, annual budgets, long-range planning) Develop self-service analytics capabilities enabling finance teams to access real-time business insights Create executive dashboards tracking key financial and operational metrics (ARR, bookings, retention, CAC, LTV) Data Engineering Analytics Infrastructure Write complex SQL queries to extract, transform, and analyze large datasets from multiple source systems Build ETL pipelines to integrate financial data from ERP, CRM, billing, and data warehouse systems Ensure data quality, consistency, and governance across financial reporting systems Optimize database performance and data architecture for scalability Strategic Analysis Insights Conduct deep-dive analyses on business performance, identifying trends, anomalies, and opportunities Support strategic initiatives through ad-hoc financial modeling and what-if scenario analysis Translate complex data findings into clear, actionable recommendations for leadership Collaborate with Data Science teams to develop advanced analytics and ML models for finance use cases Required Qualifications Technical Skills Must Have: Advanced SQL proficiency (complex joins, window functions, CTEs, query optimization) Must Have: Expert-level experience with at least one BI tool (Tableau, Power BI, Looker, or Qlik) Must Have: Advanced Excel/Google Sheets skills (pivot tables, complex formulas, data modeling) Preferred: Python or R for data analysis, automation, and statistical modeling Preferred: Experience with cloud data platforms (Snowflake, BigQuery, Redshift, Databricks) Preferred: Knowledge of ETL tools (dbt, Airflow, Fivetran) and version control (Git) Financial Business Acumen Experience in data analytics within finance, FPA, or revenue operations functions Strong understanding of financial statements (PL, balance sheet, cash flow) Knowledge of key financial metrics: ARR, MRR, bookings, revenue recognition, CAC, LTV, gross margin, EBITDA Experience with financial planning processes: budgeting, forecasting, variance analysis, scenario modeling Understanding of SaaS/subscription business ... (truncated, view full listing at source)