Hudson River Trading★4.5 (2)· London

You will work with Python, Pandas, NumPy, R, and MATLAB to apply statistical analysis and machine learning to vast quantities of market data. The team builds and maintains predictive trading models for the company's high-performance trading infrastructure. You will research, develop, and test order execution methods to increase trading efficiency.

Hudson River Trading★4.5 (2)· London

You will use Python, C++, Pandas, NumPy, R, or MATLAB to build and maintain predictive trading models. As an algorithm developer, you research and test novel order execution and model training methods, applying

Société Générale★3.8 (3.8k)· London

You will support xVA traders in derivatives pricing, exposure modelling and portfolio optimisation, working with Python, C++, R or MATLAB. You will join a Front Office xVA Trading team within Société Générale’s Fixed Income & Currencies business, contributing to pricing tools and risk management across interest rates, FX and credit asset classes.

Qube Research & Technologies, a global quantitative investment manager, seeks PhD final-year students or postdocs to develop trading algorithms and predictive signals across high, mid, and low-frequency systematic trading systems. You'll work with C++, Python, R, MATLAB, or C# to analyze vast datasets, translate theoretical models into production-ready research, and collaborate with experienced quantitative researchers in a technology-driven environment covering all liquid asset classes.

You'll develop predictive signals using statistical analysis, machine learning, NLP, and AI techniques on large datasets, working with Python, R, Matlab, or C++/C#. You'll lead the full research cycle from signal generation through implementation within QRT's global execution platform, monitoring model performance while collaborating with researchers, technologists, and traders across the organization.

Point72★3.6 (15)· London

You'll work with large datasets using languages like Python, C++, Java, R, or MATLAB to preprocess data and build predictive models for market dynamics and systematic trading. Point72 is a quantitative investment firm applying advanced statistical learning to market prediction. This internship involves feature engineering and data validation for model estimation across a small team environment.

Point72★3.6 (15)· London

Cubist Systematic Strategies, Point72's affiliate, seeks quantitative researchers to develop statistical and predictive models for systematic trading across equities, futures, and foreign exchange using languages including Python, C++, Java, R, and MATLAB. Researchers will independently conduct rigorous research into market anomalies, managing methodology selection, data collection, backtesting, and performance monitoring. Candidates should have 3-7 years of alpha-driven quantitative research experience and advanced degrees in finance, computer science, mathematics, physics, or related quantitative disciplines.

Jump Trading★3.8 (11)· London

You will work with C++, Python, and R/MATLAB in a Linux environment to develop statistical and machine learning models for profitable trading strategies. The quantitative trading team analyzes large datasets across global markets, identifying patterns to forecast price movements and build predictive models used in live trading. You'll collaborate with traders, researchers, and engineers to apply your work to Jump Trading's proprietary trading operations.