Python Quantitative Algorithmic Trading Jobs in Belmar, NJ

As a Summer Associate in the Quantitative Trading & Research Markets team at JPMorganChase, you will join a leading quantitative modeling group focused on systematic trading, financial engineering, data analytics, statistical modeling, and portfolio optimization. 

You will work closely with traders, sales, marketing, technologists, and risk managers across products and regions. You will support research and strategy deployment, client and sales engagement, product innovation, valuation and risk management, and inventory and portfolio optimization, including electronic trading and market-making activities. You will help build quantitative models, methodologies, and infrastructure to price, hedge, and trade financial products, advancing algorithmic trading and data-driven strategies such as statistical arbitrage.

ABOUT THE PROGRAM

Our Global Markets teams develop sophisticated solutions to help clients manage risk, increase returns and solve complex financial problems. We hold leadership positions across all major financial markets worldwide. This means you'll be part of a dynamic team, helping to solve a wide range of interesting business issues and will be challenged in your work every day.

Expert instructors and J.P. Morgan professionals will teach you about our history, scale, and scope of our organization today and our ambitious plans for tomorrow. We'll teach you technical and practical skills that will help you hit the ground running.

The program is an opportunity to take your career to the next level through hands-on experience, relevant skills training and valuable professional networking. Based on your individual achievements, those who successfully complete the program may receive offers of full-time employment.

Job Responsibilities

• Develop and maintain mathematical models and cutting-edge algorithms, methodologies, and supporting infrastructure.

• Value and hedge financial transactions across a range of products, from flow products to complex derivative deals.

• Support quantitative modeling and research that inform trading strategies and decision-making.

• Collaborate with trading teams to translate research insights into practical market applications.

• Partner with quantitative researchers, technologists, traders, marketing, and risk managers across teams.

• Conduct alpha research, calibrate model parameters, and optimize pricing of financial instruments to support growth and market share.

• Manage risk in existing portfolios.

REQUIRED QUALIFICATIONS, CAPABILITIES AND SKILLS 

• Enrolled in a PhD program in a relevant field (e.g., mathematics, statistics, physics, engineering, computer science, data science, or machine learning).

• Graduating between December 2027 and August 2028.

• Demonstrates computer programming experience (e.g., Python, C++, or another programming language).

• Demonstrates analytical, quantitative, and problem-solving skills.

• Demonstrates research skills (through coursework, projects, or academic work).

• Works effectively in a dynamic, collaborative environment.

• Presents findings clearly to non-technical audiences through written and verbal communication.

• Attends a college or university in the United States. 

Preferred qualifications, capabilities, and skills

• Demonstrates knowledge of options pricing theory or trading algorithms, or a demonstrated interest in finance through coursework or prior experience.

• Shows confidence and initiative to take ownership and manage projects independently.

• Applies knowledge of machine learning and data science concepts, techniques, and tools.

• Possesses advanced proficiency in any programming language.

Locations you may join:

• New York Metro 

ABOUT US

At JPMorganChase, we're creating positive change for the diverse communities we serve. We do this by championing your innovative ideas through a supportive culture that helps you every step of the way as you build your career. If you're passionate, curious and ready to make an impact, we're looking for you.

About You

A strong interest in global financial markets is essential, as are analytical and quantitative skills, flexibility, teamwork, excellent attention to detail, and the ability to handle pressure and enjoy a collaborative environment. A strong focus on science or engineering in your undergraduate studies is important.

Beyond that, what we're most interested in are the things that make you, you: the personal qualities, outside interests, and achievements beyond academia that demonstrate the kind of person you are and the perspective you could bring to the team.

What's Next?

Help us learn about you by submitting a complete and thoughtful application, which includes your resume. Your application and resume is a way for us to initially get to know you, so it's important to complete all relevant application questions so we have as much information about you as possible. To start the application, you will be prompted to enter your email address. Your email address will be used to create and maintain your profile so make sure it is one you will have long term access to. Do not use an email address with ".edu" extension as doing so could result in delays receiving updates regarding your candidacy.  

If you are advanced to the next step of the process, you'll receive another email invitation to complete a coding challenge through Hackerrank, followed by a self-recorded video assessment via HireVue. 

Both assessments are required, and your application will not be considered for further review until you have completed both of them. We strongly encourage that you apply and complete these required elements as soon as possible, since programs will close as positions are filled.  

JPMorganChase is committed to creating an inclusive work environment that respects all people for their unique skills, backgrounds and professional experiences. We will provide reasonable accommodations for applicants with disabilities. 

Visit jpmorganchase.com/careers for upcoming events, career advice, our locations and more. 

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