Quantitative Developer, Market Risk

P2P; Singapore; On-site; SGD 70,000 - 120,000; Full time

Job summary

A leading company in financial technology is seeking a Quantitative Developer to enhance risk management capabilities and develop solutions to monitor market risks. The role requires a strong programming background, a passion for quantitative research, and the ability to communicate complex ideas clearly. Ideal candidates will have significant experience in Python and financial markets, along with a proactive approach to learning and problem-solving.

Qualifications

• 3-8 years of relevant technical experience.
• CFA Charter holder or equivalent foundational financial knowledge.
• Experience with financial asset classes.

Responsibilities

• Improve capabilities to monitor, manage, and hedge market risk.
• Develop and deploy technologies for data compute and visualization at scale.
• Engage in empirical research and instrument modeling.

Skills

Python

Pandas

Polars

Numpy

Scipy

Education

Bachelors or Masters in Financial Engineering, Finance, and/or Statistics

Tools

CI/CD framework

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.

Jump Trading's risk team manages risk globally for all trading teams and is responsible for evaluating the many facets of risk across trading strategies, markets and products. One facet of risk that the firm manages is market risk.

As a Quantitative Developer, you will employ your software development skills and interest in quantitative methods and research to improve the firm's capabilities to monitor, manage, and hedge market risk across a multitude of businesses and asset classes. Some examples of these capabilities are instrument modeling, risk measurement, and empirical research. This role requires both the nimbleness to quickly attack new business needs as well as the thoughtfulness to organize and deploy data, compute, visualization, and decision-making workflows at scale.

The team is looking for someone who is passionate about agile software development, is willing to learn and deploy quantitative methodologies via code, demonstrates intellectual curiosity, and is comfortable challenging the status quo with both humility and clear communication. If you have an interest in deepening your understanding of financial markets while continue to grow your quantitative and software development skills, talk to us!

Skills You'll Need:

• At least 3-8 years of relevant technical experience required
• Strong programming experience in Python along with common packages such as Pandas, Polars, Numpy, and Scipy
• CFA Charter holder or equivalent foundational financial markets knowledge
• Bachelors or Masters degree in Financial Engineering, Finance and/or Statistics Direct experience in working with at least one financial asset class
• Practical experience in working with data at scale (whether daily or intraday)
• Experience in CI/CD framework
• Great written and verbal communication skills – good at ELI5
• Self-directed and able to take ownership of projects and responsibilities
• Experience in having to learn something substantial from scratch while on the job

Bonus Points:

• Experience in development within a distributed Linux environment
• Experience with financial instrument modeling and/or empirical research
• Familiarity with C++ Familiarity with columnar data / databases