Finance & Strategy Finance Analytics Analyst

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies - from the worlds 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 everyones reach while doing the most important work of your career.

About the team

Stripes Finance & Strategy team is hiring a Finance Analytics Analyst. This role requires a finance professional with strong FP&A capabilities technical data skills (SQL BI tools) and demonstrated AI adaptability. The individual will own financial planning variance analysis and P&L reporting for assigned business areas while using data and technology to deliver high-quality financial insights. This role reports into the Finance & Strategy Center of Excellence.

Responsibilities

Financial Planning & Analysis

• Own P&L reporting and analysis for assigned product lines business units or functional cost centers
• Lead monthly and quarterly planning forecasting and close processes
• Perform variance analysis (actuals vs. budget actuals vs. forecast period-over-period) with clear identification of root causes and business drivers
• Track and reconcile accruals vs. actuals; ensure accuracy and completeness in financial reporting
• Support annual budgeting long-range planning and scenario modeling
• Build and maintain financial models for business case analysis investment decisions and resource allocation
• Partner with business teams to provide financial perspective on operational and strategic decisions

Data Analytics & Reporting

• Write SQL queries to extract validate and analyze data from financial systems and data warehouses
• Build and maintain financial dashboards and reports using Power BI Tableau or equivalent BI tools
• Develop data models that integrate financial and operational data for planning forecasting and performance reporting
• Automate and standardize recurring reports to reduce manual effort and improve consistency
• Navigate complex high-volume data environments (trillions of transactions across products and geographies) to extract relevant financial signals
• Ensure data accuracy and consistency across all financial outputs

AI-Augmented Working

• Use AI tools (Claude Cursor Claude Code and similar platforms) as part of workflow for analysis coding report building dashboard prototyping and problem-solving
• Apply an AI-first approach to new tasks evaluate where AI can accelerate delivery before defaulting to manual methods
• Contribute to team-wide AI adoption by sharing effective workflows prompts and use cases

Business Insights & Communication

• Prepare executive-level reports on financial performance trends and key metrics with clear conclusions and recommendations
• Conduct ad-hoc analysis to support strategic initiatives and leadership decision-making
• Translate data and financial analysis into actionable business recommendations for finance and non-finance stakeholders
• Track and interpret key financial and operational metrics including revenue processing volume take rate costs margins and unit economics

Requirements

Financial & Business Skills

• 57 years of experience in FP&A financial analysis strategic finance or corporate finance roles
• Strong understanding of financial statements (P&L balance sheet cash flow) and the ability to connect them into a complete financial picture
• Demonstrated experience in budgeting forecasting variance analysis and financial planning cycles
• Working knowledge of accrual accounting revenue recognition cost allocation and reconciliation processes
• Fluency in financial metrics: revenue gross margin EBITDA operating leverage unit economics

Technical & Data Skills

• Must Have: Strong SQL skills for data extraction transformation and analysis from relational databases and data warehouses
• Must Have: Proficiency in Power BI Tableau or equivalent BI tools for dashboard development and reporting
• Must Have: Advanced Excel / Google Sheets financial modeling scenario analysis pivot tables complex formulas
• Preferred: Python or R for data analysis automation or analytical workflows
• Ability to work with large complex datasets across multiple data sources

AI Adaptability

• Must Have: Active demonstrable use of AI tools in current work candidates should be able to provide specific examples of how AI has improved their workflow output quality or speed
• Willingness and ability to continuously adopt new AI tools and methods as they become available
• Comfort using AI for coding assistance data exploration dashboard prototyping and analytical problem-solving

Mindset & Working Approach

• Ownership: Treats assigned areas as personal accountability does not wait for direction to investigate issues identify risks or surface insights
• Depth and curiosity: Goes beyond surface-level analysis to understand business context root causes and second-order implications
• Quality and accuracy: Holds a high personal standard for the correctness completeness and trustworthiness of all outputs
• Business context orientation: Understands the business model and connects financial data to what is actually happening operationally and strategically
• Clear communication: Presents financial and analytical findings to diverse audiences (finance product engineering leadership) with clarity and precision
• Speed with rigor: Operates effectively in a fast-paced environment without compromising accuracy

Preferred Experience

• Background in technology payments fintech SaaS or high-growth platform businesses
• Experience with ERP systems (NetSuite SAP Oracle) or planning tools (Anaplan Adaptive Insights Pigment)
• Exposure to data warehousing concepts and cloud data platforms (Snowflake BigQuery Redshift)
• Experience in cross-functional environments working directly with product engineering and go-to-market teams
• Experience with high transaction volume environments where data complexity is inherent