Quantitative Researcher | Trading Team

Jump Trading; Greater London; On-site; GBP 55,000 - 80,000; Full time

Benefits offered by this job

Private Medical, Vision and Dental Insurance

Travel Medical Insurance

Group Pension Scheme

Paid Parental Leave

Parking and Cycle Schemes

Job summary

Dormont Manufacturing Co is looking for a Quantitative Researcher in Greater London. The role focuses on collecting and analyzing data sets to develop profitable trading strategies. Successful candidates will have strong programming skills in C++/Python and experience with statistical models.

Benefits include private medical insurance, a group pension scheme, and paid parental leave. Collaboration and innovation drive the company's research outcomes.

Qualifications

• Proven success with profitable trading strategies.
• Strong programming skills in C++/Python in a Linux environment.
• Working knowledge of forecasting and data mining techniques.

Responsibilities

• Collect and analyze data sets to identify patterns.
• Develop forecasts and predictive trading models.
• Collaborate with scientists, traders, and developers.

Skills

Profitable trading strategies

Programming in C++/Python

Data mining techniques

Statistical models development

Machine learning

Large data sets handling

Python, R or MATLAB

Education

Masters or PhD in Statistics, Physics, Mathematics

Job description

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

The quantitative trading teams at Jump Trading probe and examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis and data mining skills, using the results of their research to make forecasts and develop profitable predictive trading models.

What You’ll Do:

Quantitative Researchers collect and analyze tens of thousands of data sets, identify patterns and extract insights into the complexities in financial markets. Researchers lean heavily on statistical analysis, machine learning, and data engineering skills; applying the results of their research to forecasts and predictive trading models. Jump’s Quantitative Researchers are constantly collaborating with other scientists, traders, hardware and software developers, and market facing business teams to push for the best expression of our new ideas. Other duties as assigned or needed.

Skills You’ll Need:

• Proven success with profitable trading strategies.
• Strong programming skills in C++/Python in a Linux environment.
• Working knowledge of forecasting and data mining techniques, such as linear and non-linear regression analysis, neural networks, or support vector machines.
• Strong experience developing statistical models in a trading environment.
• Proven success working with large data sets and developing statistical models.
• Fascinated and interested in advancing machine learning within the trading community.
• Possess strong familiarity with Python, R or MATLAB along with development skills to support research efforts.
• Masters or PhD in Statistics, Physics, Mathematics (or related subject).
• Desire to work within a collaborative, team-driven environment.
• Reliable and predictable availability

Benefits include:

• Private Medical, Vision and Dental Insurance
• Travel Medical Insurance
• Group Pension Scheme
• Group Life Assurance and Income Protection Schemes
• Paid Parental Leave
• Parking and Cycle Schemes