Quant Research Intern: ML Strategies & Portfolio Modeling

Akuna Capital; Chicago (IL); On-site; USD 130,500 - 159,500; Part time

Job summary

Akuna Capital is a trading firm focused on collaboration, technology, data-driven solutions and automation. In Chicago, the Quant team runs a 10-week Akunacademy internship, combining math, statistics and machine learning to create trading strategies for derivatives markets.

Ideal candidates are pursuing a bachelor’s, master’s or PhD in related fields, with strong ML/statistics skills, modeling experience and Python proficiency.

Qualifications

• Pursuing a bachelor's, master's or PhD in Statistics, Computer Science, Engineering, Mathematics (or a related subject)
• Expertise in statistics and machine learning
• Experience building mathematical models for complex real-world problems
• Intermediate programming skills in Python
• The ability to react quickly and accurately to rapidly changing market conditions, including the ability to quickly and accurately respond and/or solve math and coding problems are essential functions of the role
• Financial experience is not a requirement
• Must graduate by August 2028
• GPA of 3.5 or above
• Legal authorization to work in the U.S. is required on the first day of employment including F-1 students using CPT, OPT or STEM

Responsibilities

• Develop trading strategies using statistical and machine learning algorithms.
• Design and implement optimization algorithms for portfolio construction.
• Develop quantitative models describing market behavior.
• Advance existing initiatives and explore opportunities for new research topics.

Skills

Statistics

Machine learning

Python

Mathematical modeling

Education

Bachelor/Master/PhD in Statistics/CS/Engineering/Mathematics

Job description

Akuna Capital is a trading firm focused on collaboration, technology, data-driven solutions and automation. In Chicago, the Quant team runs a 10-week Akunacademy internship, combining math, statistics and machine learning to create trading strategies for derivatives markets.

Ideal candidates are pursuing a bachelor’s, master’s or PhD in related fields, with strong ML/statistics skills, modeling experience and Python proficiency.