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 FP&A 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 FP&A, 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 FP&A 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, FP&A, or revenue operations functions
- Strong understanding of financial statements (P&L, 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 models and revenue recognition principles (ASC 606 preferred)
Analytical & Problem-Solving
- Proven ability to work with large, complex datasets and derive meaningful insights
- Experience building financial models and dashboards that drive executive decision-making
- Strong statistical analysis skills and understanding of data visualization best practices
- Track record of translating ambiguous business problems into structured analytical frameworks
Preferred Experience
- Background in fintech, payments, B2B SaaS, or high-growth technology companies
- Experience supporting GTM analytics (sales forecasting, pipeline analysis, quota setting)
- Familiarity with finance systems: NetSuite, Anaplan, Adaptive Planning, Salesforce, Stripe Billing
- Exposure to data science methodologies and machine learning concepts
- Previous work in cross-functional environments collaborating with finance, data science, and business teams
Key Competencies
- Business Acumen: Ability to understand complex business models and translate them into data requirements
- Technical Excellence: Deep technical skills with commitment to code quality and best practices
- Communication: Exceptional ability to explain technical concepts to non-technical stakeholders
- Stakeholder Management: Experience partnering with senior leaders and influencing through data
- Ownership Mindset: Self-directed with ability to manage multiple priorities and drive projects to completion
- Continuous Learning: Curiosity to learn new tools, techniques, and business domains
- Attention to Detail: Commitment to data accuracy and quality in high-stakes financial reporting
Education
- Bachelor's degree in Finance, Economics, Statistics, Mathematics, Computer Science, Engineering, or related quantitative field
- Advanced degree (MBA, MS in Analytics/Data Science) or relevant certifications (CFA, CPA, data analytics certifications) a plus
What Makes This Role Unique This position sits at the intersection of data engineering, business intelligence, and strategic finance. You'll have the autonomy to architect solutions that shape how Stripe makes multi-million dollar decisions, while working with cutting-edge data technologies and some of the brightest minds in fintech. If you're energized by the prospect of building the analytics infrastructure that powers a global payments platform, this role is for you.