Stripe is hiring a Treasury Finance AI and Quantitative Analytics, Americas in 6410 Treasury Finance — NYC. The overview below is synthesized from the employer posting on stripe.com: factual requirements and scope are preserved, but prose is rewritten with editorial context. Verify details and apply via the employer link.
Who we are
About Stripe
Company context from the listing:
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.
About the team
Company context from the listing:
At its core, Stripe is a treasury company, and the Treasury Finance team is key to building the Global Payments and Treasury Network (GPTN). We collaborate closely with product, engineering, sales, and finance teams to create innovative solutions that enhance Stripe's financial capabilities.
What you’ll do
Day-to-day scope for the Treasury Finance AI and Quantitative Analytics, Americas as described in the posting:
Within Treasury Finance AI and Quantitative Analytics, you'll leverage your finance, artificial intelligence (AI), and technical expertise to build intelligent solutions that enhance Stripe's treasury capabilities. You'll develop AI-powered tools and quantitative models, autonomous agents, and analytics that automate complex workflows and provide actionable insights.
Responsibilities
Day-to-day scope for the Treasury Finance AI and Quantitative Analytics, Americas as described in the posting:
- Apply your treasury and finance domain expertise to identify high-impact opportunities where AI can be integrated with quantitative tools to solve complex treasury challenges
- Build AI-powered tools and artificial intelligence solutions to automate treasury workflows, enhance risk management, and scale our operations
- Ship interactive data products and self-service analytics tools using Python frameworks (Streamlit, Dash, Gradio) that provide real-time treasury insights and actionable intelligence
- Work across Treasury Finance and partner teams to scope AI-driven solutions that allow us to optimize and scale our most complex, data-driven financial workflows
- Develop targeted observability and performance analytics for core treasury workstreams, providing key insights to senior leadership
- Leverage heterogeneous and unstructured data to develop business insights and recommendations
- Collaborate with data scientists and engineers to build data pipelines, models, and infrastructure for core treasury workstreams
Who you are
Experience and skills the team lists as required:
The listing frames the Treasury Finance AI and Quantitative Analytics, Americas at Stripe as a hands-on product role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
Minimum requirements
Experience and skills the team lists as required:
- Bachelor’s degree in finance, mathematics, statistics, economics, engineering, or a related technical field with 6–8 years of work experience in software development, data science, or treasury and finance roles
- Working familiarity with financial risk and capital markets concepts
- Proficiency in Python and experience with AI/ML frameworks including PyTorch and TensorFlow
- Experience with Large Language Model (LLM) frameworks such as LangChain, LangGraph, or similar tools for building AI applications and agentic systems
- Solid understanding of AI fundamentals, including deep learning, natural language processing, and generative AI
- Results-oriented, with a focus on delivering impact in a fast-paced environment
- Excellent communication skills for collaborating with finance, product, and engineering teams
- Highly organized, with attention to detail and the ability to manage tight deadlines
Preferred qualifications
Experience and skills the team lists as required:
- Familiarity with the payments industry and fintech landscape
- Experience with Databricks and cloud platforms (AWS, GCP, Azure)
- Good understanding of development processes and best practices across engineering standards, code reviews, and testing