Fixed Income Quantitative Researcher | Trading Team

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 quantitative research team combines deep expertise in mathematics, statistics, and computer science to develop data-driven proprietary models for market prediction and risk management. The team emphasizes rigorous empirical research, incorporating statistics and modern data-science techniques alongside traditional signal processing to extract patterns from large, noisy datasets and improve predictive performance.

This role sits within a specialist team of fixed income experts, operating as part of a larger futures, equity, and options group. You will have direct access to deep asset-class knowledge while benefiting from the shared infrastructure, cross-asset datasets, and research culture of a much broader trading organization.

What you will do:

• Develop and refine quantitative models that predict and trade fixed income products, focusing on medium- to long-frequency alpha - signals with typical holding periods ranging from several hours to several days - as well as manage portfolio risk
• Analyse market data, investigating the relationship between market events and product price movements to identify trading opportunities and optimize strategies using statistical and mathematical techniques
• Build predictive models on large-scale, noisy financial time series - designing, training, and validating signals that hold up out of sample, and monitoring them in production
• Collaborate with the wider futures, equity, and options group to share signals, data, and infrastructure, and to implement efficient algorithms alongside technologists and traders
• Ensure accurate risk assessment and real-time decision-making in a dynamic market environment
• Skills you will need: Familiarity with fixed income concepts, including but not limited to bond and interest rate swap pricing, yield curve analysis, and algo optimization
• Demonstrated experience researching predictive signals at multi-hour to multi-week horizons - including signal construction, backtesting, turnover and capacity analysis — rather than purely latency-driven strategies
• Deep expertise in at least one of: modern deep learning (sequence models, transformers, representation learning, with PyTorch/JAX or equivalent), Bayesian time series, or high-dimensional statistics - with a clear understanding of how to avoid overfitting in low signal-to-noise regimes
• Proven success working with large datasets in academic projects or a professional environment
• Strong problem-solving, statistics, and mathematics skills
• Solid Python along with the software development skills to support research efforts
• Good C++ skills are a plus
• Master's or PhD in mathematics, statistics, operations research, physics, computer science, financial engineering, or a related subject
• Desire to work within a collaborative, team-driven environment