Investment Research Intern - Summer 2027, Stamford

Hedgeye Risk Management, LLC; Stamford (CT); On-site; USD 34,000 - 41,000; Full time

Job summary

Hedgeye Risk Management invites undergraduates to join the Summer 2027 Research Internship Program in Stamford, CT. Interns work full-time for ten weeks, collaborating with sector research teams on data analysis, modeling, and report drafting.

Program includes career and industry workshops, mentorship, and a final stock pick presentation. Strong quantitative skills, Excel proficiency, and Python familiarity preferred.

Qualifications

• Current undergraduate junior with an expected graduation date in 2028 (preferred)
• Minimum GPA of 3.0 or higher
• Strong quantitative and analytical skills
• Excellent written and oral communication abilities
• Advanced proficiency in Microsoft Excel
• Experience with financial modeling
• Familiarity with programming languages such as Python (preferred)
• Adaptability, attention to detail, and the ability to work both independently and as part of a team

Responsibilities

• Work directly with sector research teams contributing to data and statistical analysis, independent projects, information synthesis, and drafting of reports.
• Help with financial modeling and presentation of research findings.
• Deliver a final stock pick presentation assigned by the research team at program end.
• Attend workshops and receive mentorship from the broader research team.

Skills

Quantitative analysis

Financial modeling

Written communication

Oral communication

Python experience

Education

Undergraduate student (junior)

Tools

Microsoft Excel

Python

Job description

Hedgeye Risk Management invites undergraduates to join the Summer 2027 Research Internship Program in Stamford, CT. Interns work full-time for ten weeks, collaborating with sector research teams on data analysis, modeling, and report drafting.

Program includes career and industry workshops, mentorship, and a final stock pick presentation. Strong quantitative skills, Excel proficiency, and Python familiarity preferred.