Quantitative Research Intern

02 · Requirements and your timeline

Check the actual eligibility requirements.

Degree levels recorded

bachelors · masters · phd

Graduation window

December 2027–August 2028

Start date

Not confirmed

Deadline

No fixed deadline confirmed

Minimum years of experience

No numeric minimum confirmed

No fixed application closing date is published in the reviewed JD or job-specific ATS application metadata; apply promptly and reconfirm before submitting.

Bachelor’s/master’s/PhD in a technical quantitative discipline graduating December 2027–August 2028. Python scientific stack, large datasets, statistics, probability and numerical methods. U.S. locations: Chicago and New York City.

• Role-specific sponsorship and CPT/OPT support are not confirmed.
• This is a specialized quantitative-finance internship, not a general DA role.
• The title does not state the internship year; the body supplies the 2027–2028 graduation window.

Questions still to resolve

• Confirm sponsorship for the specific role and your circumstances.
• Add your graduation month and year to compare the published window.
• Confirm enrollment in the degree program specified by this posting.
• E-Verify enrollment has not been matched to the hiring legal entity. Verify separately if relevant to STEM OPT.
• Compare your degree and enrollment status with the official requirements.
• No fixed deadline was confirmed; check the official posting before applying.

Graduation dates are compared only where exact bounds are stated. We do not infer CPT/OPT eligibility, work permission or H-1B timing from your academic year.

03 · Separate employer check

E-Verify

Hiring legal entity not independently confirmed

No official E-Verify legal-employer match was verified for this posting. A general E-Verify notice is not a legal-entity match or proof of H-1B support.

E-Verify participation is separate from H-1B sponsorship and the other STEM OPT requirements. An employer statement or an unmatched name is not a completed legal-employer verification.

04 · Prepare with a purpose

What to prepare and why

Why prepare: the role applies statistics and ML to market research, simulation and model validation. Preparation: implement a transparent research notebook with time-based validation and explain assumptions, numerical methods and failure cases.