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Quantic Quantitative Researcher Intern (Summer 2027)


Job Location:

Boston, MA - USA

Monthly Salary: Not provided by the employer
Posted: 3 June 2026 (30+ days ago)
Application Deadline: 17 October 2026
Vacancies: 1 Vacancy
The job posting is outdated and position may be filled

Job Summary

Position: Quantic - Quantitative Researcher Intern (Summer 2027)

Location: Boston MA

Please apply to only one opportunity between the Quantitative Developer Quantitative Researcher and PhD Quantitative Researcher positions with Quantic. If the team finds you could be a potential fit for the other we will contact you.

Firm Overview:

Walleye Capital is a $16 billion multi-strategy investment firm headquartered in New York City with over 350 employees across five main offices. Founded in 2005 as an options market maker we have organically grown into a global investment firm specializing in Quant Fundamental Equities and Volatility strategies.

Our Team Overview:

Walleye Capital is seeking highly quantitative and creative Quantitative Researcher Interns to work in the rapidly growing Quantic team based out of Boston. Quantic is Walleyes principal quantitative investment business established in 2016 as one of its core investment strategies. Quantic has subsequently evolved into one of the most successful trading teams in the industry.

We are a tight-knit collaborative and intellectually rigorous group of scientists engineers and traders leveraging advanced statistical modeling techniques to identify and capitalize on profitable trading opportunities in global equities options and futures. What sets Quantic apart is our pragmatic engineering-driven culture where achieving goalsand achieving them the right waytakes precedence. We foster collaboration among colleagues confident that the best ideas arise through cross-disciplinary exchange. Our commitment to continuous self-reflection and growth drives us to build the strongest possible platform for our teams future success. We are seeking talented researchers to help elevate our capabilities and join us on this journey.

This role offers the opportunity to engage directly with cutting-edge data analysis portfolio optimization platform development and operation of fully automated trading systems. You will join a team where your creativity initiative and teamwork will make direct impacts on trading profits for our investors. We invite researchers with a proven record of innovation and achievement in their fields to apply.

Position Overview:

As a Quantic Intern youll work directly with experienced team members on meaningful projects that impact trading strategies and operations. Youll have the opportunity to work on high-impact initiatives and develop your skills in a dynamic setting where innovation teamwork and talent drive success.

We are seeking students with strong technical backgrounds (e.g. mathematics statistics computer science or engineering) demonstrated initiative and an interest in quantitative trading and research. Successful interns are curious collaborative and eager to tackle complex problems in a fast-paced supportive environment.

The internship is 10 weeks in length and will take place in Boston from June to August 2027.

Responsibilities:

  • Research design and test predictive signals data sets and systematic trading strategies.
  • Extract and analyze large datasets from structured and unstructured sources applying advanced statistical and computational methods.
  • Enhance research infrastructure and tools for trading risk management and attribution.
  • Develop machine learning models to predict patterns in asset returns risks trading costs or other portfolio-relevant variables.
  • Design and implement scalable code across various stages of the investment process.
  • Work in Python and/or R with opportunities to contribute to research tools and libraries.
  • Leverage AI tools including LLM-based analytical pipelines to enhance processes and analyses.

We seek individuals who:

  • Are pursuing an undergraduate or advanced degree in computer science engineering statistics mathematics or a related field with an expected graduation date between December 2027 and June 2028.
  • Possess strong programming skillsparticularly in Python or Rand hold experience working with large datasets APIs or databases.
  • Demonstrate rigorous analytical thinking statistical modeling abilities and familiarity with techniques from machine learning optimization or time-series analysis.
  • Are self-starters who enjoy digging into complex open-ended problems and can work both independently and collaboratively with a team.
  • Exhibit a genuine interest in financial markets systematic investing AI/LLM application and using technology in dynamic data-rich environments.
  • Showcase creativity and enthusiasm for leveraging AI tools to enhance productivity improve processes and generate investment alpha.
  • Thrive in a collaborative culture that values intellectual humility creativity and continuous learning.

Pay Range:

The expected monthly pay for this position is $20000/month. Interns will also receive a $10000 housing stipend and transportation to and from Boston (domestic travel only).

The deadline to apply for this opportunity is Friday July 31 at 11:59pm ET. For questions about the process please review ourCampus FAQs.

Please apply to only one opportunity between the Quantitative Developer Quantitative Researcher and PhD Quantitative Researcher positions with Quantic. If the team finds you could be a potential fit for the other we will contact you.

Walleye is an equal opportunity employer. Individuals seeking employment are considered without regard to race color religion national origin age sex marital status ancestry physical or mental disability veteran status sexual orientation or any other category protected by applicable law.

If you require a reasonable accommodation to participate in any part of our hiring process please contact .

Personal data you provide will be processed in accordance with Walleye Capital LLCs Privacy Notice available at:


Required Experience:

Intern