Quantitative Research Intern: Systematic Trading

Point72; Greater London; On-site; GBP 89,000 - 133,000; Part time

Job summary

Point72 is offering an internship opportunity for students and researchers focused on advanced data modeling and statistical learning applied to market prediction and systematic trading.

The role involves preprocessing large data sets, feature engineering, and developing predictive models. Candidates should be advanced undergraduates, MS, or PhD students in quantitative fields with strong programming skills and a passion for financial markets.

Qualifications

• Pre-process (validate, clean, normalize, reduce dimension) very large data sets for model estimation and event studies.
• Identify features and relationships useful for predictive modeling of market dynamics.
• Undergraduate, MS, or PhD candidates in finance, CS, mathematics, physics, or other quantitative discipline.
• Programming in C++, Java, C#, MATLAB, R, Python, or Perl.
• Strong analytical and quantitative skills.
• Demonstrated interest in financial markets and systematic trading.
• Clear, concise, and proactive communicator.
• Detail-oriented.
• Willing to take ownership of work, both independently and in a small team.

Responsibilities

• Pre-process very large data sets for model estimation and event studies.
• Identify features and relationships useful for predictive modeling of market dynamics.
• Undergraduate, MS, or PhD candidates in quantitative disciplines.
• Programming in C++, Java, C#, MATLAB, R, Python, or Perl.
• Demonstrate strong analytical and quantitative skills.
• Show interest in financial markets and systematic trading.

Skills

Data modeling

Statistical learning

Programming

Analytical thinking

Financial markets interest

Communication

Detail-oriented

Ownership mindset

Education

Undergraduate, MS, or PhD candidates (finance, CS, math, physics)

Tools

C++

Java

C#

MATLAB

R

Python

Perl

Job description

Point72 is offering an internship opportunity for students and researchers focused on advanced data modeling and statistical learning applied to market prediction and systematic trading.

The role involves preprocessing large data sets, feature engineering, and developing predictive models. Candidates should be advanced undergraduates, MS, or PhD students in quantitative fields with strong programming skills and a passion for financial markets.