Quantitative Research Intern: Systematic Trading

Quantitative Research Intern: Systematic Trading

Full-Time 22500 - 27500 Β£ / year (est.) No working from home possible
Point72

At a Glance

  • Tasks: Preprocess large data sets and develop predictive models for market trading.
  • Company: Point72, a leading firm in systematic trading and data analysis.
  • Benefits: Gain hands-on experience, mentorship, and networking opportunities in finance.
  • Other info: Exciting internship with potential for future career opportunities in finance.
  • Why this job: Dive into the world of finance and enhance your data skills with real market impact.
  • Qualifications: Advanced undergraduates or postgraduates in quantitative fields with strong programming skills.

The predicted salary is between 22500 - 27500 Β£ per year.

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 Ph D students in quantitative fields with strong programming skills and a passion for financial markets.

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Quantitative Research Intern: Systematic Trading employer: Point72

Point72 is an exceptional employer that prioritises the well-being and professional growth of its employees in the heart of London. With comprehensive benefits including private medical insurance, generous family leave, and wellness programmes, we foster a supportive work culture that encourages career development within a dynamic global investment firm. Join us to be part of a team that values compliance excellence and offers unique opportunities for advancement.

Point72

Contact Details:

Point72 Recruitment Team

We think you need these skills to ace Quantitative Research Intern: Systematic Trading

Data Modelling
Statistical Learning
Market Prediction
Systematic Trading
Data Preprocessing
Feature Engineering
Predictive Modelling