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Treasury Quantitative Analyst Jobs (NOW HIRING)

StradIT

Quantitative Analyst - US

Jersey City, NJ · On-site

Knowledge of treasury securities and/or mortgage-backed securities pricing and VaR modeling a big plus * Strong analytical and problem-solving skills * Excellent communication skills, both oral and ...

Stradit LLC

Quantitative Analyst - US

Jersey City, NJ · On-site

Knowledge of treasury securities and/or mortgage‑backed securities pricing and VaR modeling a big plus * Strong analytical and problem‑solving skills * Excellent communication skills, both oral ...

corpay

Quantitative Risk Analyst

Salt Lake City, UT · Hybrid

In this role, you will sit behind Corpay's proprietary Treasury Management System (TMS) suite ... How We Work As a Quantitative Risk Analyst you will be expected to work in a hybrid environment.

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How much do treasury quantitative analyst jobs pay per year?

As of Sep 11, 2026, the average yearly pay for treasury quantitative analyst in the United States is $78,779.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,500.00 and $93,000.00 per year, depending on experience, location, and employer.

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Infographic showing various Treasury Quantitative Analyst job openings in the United States as of September 2026, with employment types broken down into 8% Internship, and 92% Full Time. Highlights an 62% In-person, 23% Hybrid, and 15% Remote job distribution, with an average salary of $78,779 per year, or $37.9 per hour.

Treasury Finance AI and Quantitative Analytics, Americas

New York, NY • On-site

Stripe
Software Development • 1 - 5K employees
Learn more about Stripeexternal

Full-time

Re-posted 18 days ago

Job description

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
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. As part of Treasury Finance's AI and Quantitative Analytics team, you'll work at the intersection of finance, artificial intelligence, quantitative reasoning, and product development, building autonomous agents and intelligent solutions that enhance treasury capabilities and enable us to better serve and scale with the global economy.
What you'll do
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. Working at the intersection of artificial intelligence, finance, and product development, you'll collaborate with engineering and finance teams to deploy cutting-edge AI applications that scale with Stripe's growth and support our mission of increasing the GDP of the internet.
Responsibilities
  • 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
We're looking for a technical problem-solver with treasury, quantitative reasoning, and finance expertise who's excited about leveraging artificial intelligence and 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.
Minimum requirements
  • 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
  • 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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