# Treasury Finance AI and Quantitative Analytics, Americas

**Company:** [Stripe](https://hotfix.jobs/companies/stripe)
**Location:** New York, NY
**Role:** ML Engineering
**Experience:** 6+ years
**Skills:** Python, PyTorch, TensorFlow, LangChain, LangGraph, streamlit, dash, gradio, AWS, GCP, Azure, Databricks
**Posted:** 2026-07-24

> Build AI-powered tools, quantitative models, autonomous agents, and analytics to automate treasury workflows, enhance risk management, and deliver insights at Stripe. Requires 6-8 years experience, Python proficiency, AI/ML frameworks, and treasury/finance expertise.

## Job Description

## Responsibilities
- Apply 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 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 optimization and scaling of 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.

## Minimum Requirements
- Bachelor’s degree in finance, mathematics, statistics, economics, engineering, or a related technical field.
- 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
- 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.

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