Quantitative Trading & Research: AI/ML for CIB Treasury

JPMorgan Chase; New York (NY); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Health care coverage

Retirement savings plan

Tuition reimbursement

On-site wellness centers

Job summary

JPMorganChase's Quantitative Trading & Research (QTR) team seeks an Associate/VP to tackle technically complex business problems, from leveraging LLMs to delivering ML applications at scale and handling large datasets using the firm's cloud capabilities.

You will partner with business leads to identify pain points, prototype solutions, and present results to stakeholders, driving data strategy and supporting revenue growth with quantitative methods.

Qualifications

• Advanced degree in a quantitative field (PhD or MS) required.
• Strong ML, statistics, and math fundamentals with practical application.
• Experience delivering end-to-end data science projects in Python.

Responsibilities

• Work with business leads to develop AI/ML-driven analytics and automation that support their business goals.
• Build a scalable data architecture to handle large volumes of transaction data.
• Automate manual processes and build tools to optimize decision making and deposit management.
• Develop sequential decision-making tools to optimize net interest income under liquidity and balance sheet constraints.
• Drive projects end-to-end from brainstorming to model development.
• Present real-world, commercial recommendations to stakeholders with impact.
• Visualize data to communicate quantitative insights for business decisions.

Skills

Quantitative degree

ML & Stats

Python

Communication

Education

PhD/MS in quantitative field

Tools

Python

Job description

JPMorganChase's Quantitative Trading & Research (QTR) team seeks an Associate/VP to tackle technically complex business problems, from leveraging LLMs to delivering ML applications at scale and handling large datasets using the firm's cloud capabilities.

You will partner with business leads to identify pain points, prototype solutions, and present results to stakeholders, driving data strategy and supporting revenue growth with quantitative methods.