Summer Quant Research & Trading Internship

Trading Interview; Greater London; Hybrid; GBP 8,900 - 13,000; Full time

Benefits offered by this job

Fully stocked pantry

Weekly trading/research meetings

Graduate role consideration

Job summary

XY Capital is seeking driven STEM students for a 10-week internship with a hands-on role in building models, researching market behavior, and enhancing trading strategies. You will collaborate with Traders and Quant Researchers to identify alpha and execute models across asset classes.

The program emphasizes rigorous research methods, Python proficiency (Pandas, Sci-Kit Learn, XGBoost, TensorFlow), and a team-based environment.

Qualifications

• Pursuing a STEM degree (undergrad/ masters/ PhD).
• Graduating Summer/Winter 2027 or Summer 2028.
• Strong understanding of research methodology and techniques.
• Proficiency in Python with libraries (Pandas, Sci-Kit Learn, XGBoost, TensorFlow).
• Experience with ADRs/GDRs or US/EMEA equities trading/research is a bonus.
• Experience in small, collaborative teams.
• Excellent communication and interpersonal skills.
• Proficiency in English is a must.
• Right to work in the United Kingdom for the duration of the internship.
• Available to work full-time during the internship.

Responsibilities

• Work with traders and researchers to develop models that identify alpha.
• Develop and evaluate trading strategies and analyze market behavior.
• Contribute to XY Capital’s trading capabilities during the 10-week program.

Skills

Python proficiency

Research mindset

Team player

Self-starter

English communication

Education

STEM degree (undergrad/ MSc/PhD)

Tools

Pandas

Sci-Kit Learn

XGBoost

TensorFlow

Job description

XY Capital is seeking driven STEM students for a 10-week internship with a hands-on role in building models, researching market behavior, and enhancing trading strategies. You will collaborate with Traders and Quant Researchers to identify alpha and execute models across asset classes.

The program emphasizes rigorous research methods, Python proficiency (Pandas, Sci-Kit Learn, XGBoost, TensorFlow), and a team-based environment.