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.