Stripe
Publicado originalmente en greenhouse · Aplica desde el sitio de la empresa para mejor experiencia.
<h2>Who we are</h2> <h3>About Stripe</h3> <p>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.</p> <h3>About the team</h3> <p>The Infrastructure Finance and Strategy team is an integral thought partner to Stripe's engineering leadership. We bring understanding and predictability to Stripe's R&D investments and operating expenses. We work cross-functionally across many surfaces at Stripe and help ensure the durability of our long-term financial performance.</p> <h2>What you'll do</h2> <p>We're looking for a Finance and Strategy Partner to join our growing team. You'll help us with the forecasting, budgeting, and reporting for AI investments, including token spend, engineering headcount, and management tools. You'll collaborate with data science, engineering, and finance teams to deliver improvements in our integrated financial systems and metrics, and help drive our strategies for productivity improvement and cost efficiency.</p> <h3>Responsibilities</h3> <p>• Leverage your financial background to support and influence key strategic and business decisions</p> <p>• Be your business teams' financial partner for analysis and evaluation of strategic projects and initiatives (e.g. foundational investments or business model shifts)</p> <p>• Design and provide analytical rigor to measure efficiency and ROI of investments in headcount and non-headcount expenses</p> <p>• Drive reporting, process, and discipline for finance routines to shape and influence decision-making (e.g. budget, forecast, monthly reviews, long-range plans)</p> <p>• Build and own models for in-depth analyses, as well as ensure their quality, timeliness, and accuracy</p> <p>• Partner with cross-functional teams, such as Finance Systems, Data Science, and Infrastructure Engineering, to develop reporting dashboards</p> <p>• Drive continuous process improvement, standardization, simplification, and reporting enhancements</p> <h2>Who you are</h2> <p>We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.</p> <h3>Minimum requirements</h3> <p>• 7–9 years of relevant experience in strategic finance or FP&A</p> <p>• Demonstrated experience driving and executing on finance processes (e.g. budget and forecast creation, contract negotiations, headcount envelope management)</p> <p>• Demonstrated experience using AI tools (coding agents, skills, forecasting tools) to develop data visualizations and explore datasets and developing expertise in new tools quickly</p> <p>• Fluency in AI cost drivers and metrics, including token caching, reads, and writes, model selection principles, and billing frameworks</p> <p>• Deep understanding of expense accounting principles including accruals, amortization, and capitalization</p> <h3>Preferred qualifications</h3> <p>• Experience working in corporate finance at a high-growth technology company</p> <p>• Experience managing headcount and operating expenses</p> <p>• Experience supporting engineering teams</p> <p>• Experience with Oracle, Anaplan, or similar financial management applications</p> <p>• Experience with Claude Code, Codex, Cursor, or similar coding agents</p> <p>• Experience in data visualization and dashboarding</p> <p>• Background in investment banking, private equity, corporate development, or consulting</p> <p>• Strong knowledge of G Suite tools and extracting, analyzing, and evaluating information from large data sets using SQL and large language models</p>