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Internship Risk Quant Jobs in New York (NOW HIRING)

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Internship Risk Quant information

What is an internship risk quant?

Internship Risk Quants are students or recent graduates who take on temporary roles within financial institutions to assist with quantitative analysis related to risk management. Their main responsibilities include analyzing financial data, developing risk models, and helping identify potential risks for the company. These internships provide hands-on experience with statistical tools, programming, and risk assessment in real-world finance environments. The goal is to prepare interns for full-time quantitative risk analyst roles after graduation.

What types of projects does an internship risk quant typically work on, and how do these projects contribute to the overall risk management strategy of the firm?

Risk Quant interns often work on projects involving data analysis, model validation, and the development of risk assessment tools under the guidance of senior quants. These projects may include tasks such as back-testing risk models, analyzing large datasets to identify potential risk exposures, and automating reporting processes. By contributing to these initiatives, interns help improve the firm's ability to measure and manage financial risks, gaining practical experience with real-world quantitative finance tools and methodologies. Collaboration with teams like trading, risk management, and IT is common, offering interns broad exposure to how quantitative analysis supports strategic decision-making in the organization.

What are the key skills and qualifications needed to thrive as an internship risk quant, and why are they important?

To thrive as an Internship Risk Quant, you typically need strong quantitative skills, a solid background in mathematics, statistics, or finance, and progress towards a relevant degree such as in quantitative finance or a related field. Familiarity with programming languages like Python, R, or MATLAB, as well as experience with risk management systems and financial modeling tools, is highly valued. Attention to detail, analytical thinking, and effective communication skills help interns collaborate and present complex findings clearly. These capabilities are critical for analyzing risk data accurately and supporting decision-making in dynamic finance environments.

What is the difference between Internship Risk Quant vs Risk Analyst?

AspectInternship Risk QuantRisk Analyst
Required CredentialsTypically pursuing or recent graduate, some quantitative courseworkBachelor's or master's in finance, economics, or related field; certifications like FRM or CFA often preferred
Work EnvironmentInternship setting, often in financial institutions or asset management firmsFull-time role in banks, hedge funds, or investment firms
Industry UsageCommonly used for entry-level or internship positions in risk managementEstablished role for ongoing risk assessment and management

The main difference is that an Internship Risk Quant is an entry-level, temporary position aimed at gaining experience, while a Risk Analyst is a full-time professional role responsible for ongoing risk evaluation within financial organizations.

What are the most commonly searched types of Risk Quant jobs in New York?

The most popular types of Risk Quant jobs in New York are:

What job categories do people searching Internship Risk Quant jobs in New York look for?

The top searched job categories for Internship Risk Quant jobs in New York are:

What cities in New York are hiring for Internship Risk Quant jobs?

Cities in New York with the most Internship Risk Quant job openings:

Campus Quantitative Researcher, PhD (Intern)

Jump Trading

Manhattan, NY โ€ข On-site

Other

Re-posted 9 days ago


Job description

Campus Quantitative Researcher, PhD (Intern)

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

Our trading teams are each comprised of a dynamic group of traders, quantitative researchers, and engineers who work together to examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis and data mining skills, using the results of their research to make forecasts and develop profitable predictive trading models.

About the Role

The PhD quant research internship is an intensive 10-week program designed to show you what it's like to do research at Jump: real problems, real data, real markets. The program runs in person during Summer 2027 in our Chicago and New York offices. The first two weeks are focused training covering our research process, machine learning, statistics, trading and market mechanics, Python, and the infrastructure you'll use all summer. From there, you'll be matched with a trading team based on your background and interests, and spend the remaining weeks working 1:1 with experienced researchers on a real-world project tied to live business needs. You'll learn the craft working alongside people who have spent years practicing it.

Research at Jump spans every asset class and a full range of time horizons, from high frequency to strategies that hold for days and weeks. Teams work across the spectrum of methods, from hand-crafted signals and rigorous classical statistics to deep learning models in production. Your project will reflect your team's needs, but the craft is the same everywhere: form well-educated hypotheses, construct rigorous tests, interpret results in a statistically sound way, and when an idea fails, understand why before moving on. One excellent, fully understood result is worth more here than a dozen shallow ideas. And every result is tested where it counts: against the live market itself.

The program is open to currently enrolled PhD students. The internship is one of the main pathways to a full-time offer at Jump Trading.

What You'll Do
  • Match with a trading team and own a research project end to end, in areas such as predictive modeling, alpha research on new datasets, and improving the models and systems behind live trading
  • Collect, clean, and explore large datasets (some clean, some noisy, some very noisy) and engineer features that turn raw data into predictive signal
  • Build, fit, and evaluate models on our supercomputing grid, and present your results to your team throughout the summer, culminating in a final presentation
  • Receive daily 1:1 mentorship from experienced quant researchers, with growing autonomy and compute as the summer progresses
  • Other duties as assigned or needed.
Skills You'll Need
  • Currently pursuing a PhD in Statistics, Mathematics, Computer Science, Physics, or any highly quantitative field; recent researchers have come from fields as varied as Electrical Engineering, Operations Research, and Economics
  • Systematic research thinking: the ability to form well-educated hypotheses, design rigorous tests, and draw statistically sound, generalizable conclusions. No matter your area, these are the fundamental aspects of a good researcher, and it is no different at Jump Trading.
  • Ownership of your research: the ability to explain the choices you made, the alternatives you considered and rejected, and why your approach won. Every idea demands a premise, and every rejection deserves a reason
  • Experience conducting an in-depth research project with real-world data
  • Programming experience in Python, with the ability to read, understand, and debug code, including code you didn't write
  • Communicative and collaborative working style, sharing results early and often and treating mentors' time as a resource to use, not conserve
  • Creativity and initiative to explore ideas beyond those suggested to you, with the judgment to bring your team along as you do
  • Perseverance: successful research is the result of lots of failure and intellectual risk-taking, and a PhD is often proof that you can stay with a hard problem for years without quitting
  • Reliable and predictable availability required

Nice to have:

  • Proficiency in C++ and/or Python (either works, and both is better)
  • Familiarity with financial markets. No prior knowledge of finance or trading is necessary; we will give you the training that you need.

INTERNATIONAL STUDENTS are encouraged to apply. We accept students eligible for CPT/OPT and we sponsor work visas for full-time positions.

The estimated base salary for this role is $300,000 per year.