Quant Research Intern – ML & Trading

Virtu Financial; Dublin; On-site; EUR 17,000 - 26,000; Full time

Benefits offered by this job

Daily catered lunches

Onsite gym

Laundry service

Breakfast & lunch

Games room

Job summary

Virtu Financial in Dublin offers a 10-week Quantitative Strategist Internship to learn our world of finance through hands-on research and engineering tasks.

Interns tackle real quantitative problems, gain mentorship from senior team members, and work on projects spanning quantitative research, algorithm development, and market analysis. Training is ongoing during the summer with practical output and collaboration.

Qualifications

• Advanced degree in a quantitative field (CS, DS, Math, Stats, Eng, Physics).
• History of diverse, challenging coursework with a strong GPA.
• Exceptional quantitative, mathematical, analytical, and problem-solving skills.
• Strong programming skills, particularly in Python and/or C/C++.
• Experience with data analysis libraries such as Pandas, NumPy, or similar.
• Experience with machine learning and/or deep learning frameworks (e.g., PyTorch, TensorFlow, JAX) is desirable.
• Familiarity with statistical modeling, optimization, or modern AI techniques is desirable.
• Great communication skills and the ability to collaborate with peers.

Responsibilities

• Work on real-world research and engineering problems across quantitative topics.
• Collaborate with senior team members on projects spanning ML and trading research.
• Model data and develop algorithms to improve Virtu’s trading systems.

Skills

Python

C/C++

Pandas

NumPy

Machine learning

Deep learning

Communication

Team collaboration

Statistical modeling

Education

Advanced degree in Computer Science, Data Science, Mathematics, Statistics, Engineering, Physics

Tools

PyTorch

TensorFlow

JAX

Job description

Virtu Financial in Dublin offers a 10-week Quantitative Strategist Internship to learn our world of finance through hands-on research and engineering tasks.

Interns tackle real quantitative problems, gain mentorship from senior team members, and work on projects spanning quantitative research, algorithm development, and market analysis. Training is ongoing during the summer with practical output and collaboration.