Quant Researcher: ML-Driven Trading & Forecasting

Trading Interview; Amsterdam; Hybrid; EUR 90,000 - 150,000; Full time

Benefits offered by this job

Travel Medical Insurance

Group Life Assurance

Income Protection Schemes

Job summary

Jump Trading Group is a leading quantitative research firm focused on world-class data science and market research. This role develops and tests forecasting models, statistical analyses, and ML approaches to improve trading decisions.

You will collaborate with traders, scientists, and software engineers to push the envelope on research-driven strategies, with a strong emphasis on data integrity and rigorous methods.

Qualifications

• Proven track record of profitable trading strategies.
• Strong programming in C++ and Python in Linux environments.
• Experience with forecasting, data mining, and ML techniques.
• Experience building statistical models for trading.
• Ability to handle large data sets and deliver insights.
• Interest in advancing machine learning within trading.
• Proficiency in Python, R or MATLAB for research support.
• Master's or PhD in relevant fields is preferred.

Responsibilities

• Collect and analyze large data sets to extract trading insights.
• Develop forecasting models and predictive trading strategies.
• Collaborate with scientists, traders, and software teams to implement ideas.
• Advance machine learning techniques within the trading domain.

Skills

Profitable trading strategies

C++

Python

Linux

Forecasting

Data mining

Regression analysis

Neural networks

Support vector machines

Statistical models

Large data sets

Machine learning

R

MATLAB

Team collaboration

Reliability

Education

Master's or PhD in Statistics/Physics/Mathematics

Tools

Linux

Job description

Jump Trading Group is a leading quantitative research firm focused on world-class data science and market research. This role develops and tests forecasting models, statistical analyses, and ML approaches to improve trading decisions.

You will collaborate with traders, scientists, and software engineers to push the envelope on research-driven strategies, with a strong emphasis on data integrity and rigorous methods.