Our Quantitative Researchers use mathematics, statistics, machine learning and rigorous experimentation to understand how markets behave and turn research into trading strategies and decisions at global scale.
They develop hypotheses, build and test models, translate mathematical ideas into code and learn from measurable results in live markets.
Our Quantitative Researchers use mathematics, statistics, machine learning and rigorous experimentation to understand how markets behave and turn research into trading strategies and decisions at global scale.
They develop hypotheses, build and test models, translate mathematical ideas into code and learn from measurable results in live markets.
Quantitative Research at Citadel Securities sits at the intersection of statistical inference, large-scale computing and market microstructure.
Researchers work with large-scale, varied data and advanced modeling techniques to identify patterns, test hypotheses and build models that inform real-time decisions. Markets are non-stationary: relationships decay, regimes shift, and a result only counts once it holds under realistic costs, latency and capacity limits.
Our researchers work across the lifecycle, from hypothesis and experimentation through validation and deployment, in close partnership with engineers and traders. Once a model or strategy moves into live trading, market feedback provides clear, measurable evidence that informs the next iteration.
Quantitative Research at Citadel Securities sits at the intersection of statistical inference, large-scale computing and market microstructure.
Researchers work with large-scale, varied data and advanced modeling techniques to identify patterns, test hypotheses and build models that inform real-time decisions. Markets are non-stationary: relationships decay, regimes shift, and a result only counts once it holds under realistic costs, latency and capacity limits.
Our researchers work across the lifecycle, from hypothesis and experimentation through validation and deployment, in close partnership with engineers and traders. Once a model or strategy moves into live trading, market feedback provides clear, measurable evidence that informs the next iteration.
Different problems, one research-to-trading pipeline.
Develop and test models that seek to explain and forecast market behavior. Researchers combine market intuition, statistical methods and machine learning to identify signals, understand how they behave and translate successful ideas into production.
Turn forecasts into trading strategies. Researchers design the logic behind position sizing, risk, transaction costs, capacity and the other real-world constraints that shape how those ideas perform.
The method follows the problem. Our researchers draw from a broad and evolving set of techniques—including deep learning, foundation and generative models, representation learning, multimodal methods and LLM-driven tools—to tackle problems across forecasting, market-state estimation, simulation, signal extraction and the research process itself. AI and ML are integrated throughout the research lifecycle.
Different problems, one research-to-trading pipeline.
Develop and test models that seek to explain and forecast market behavior. Researchers combine market intuition, statistical methods and machine learning to identify signals, understand how they behave and translate successful ideas into production.
Turn forecasts into trading strategies. Researchers design the logic behind position sizing, risk, transaction costs, capacity and the other real-world constraints that shape how those ideas perform.
The method follows the problem. Our researchers draw from a broad and evolving set of techniques—including deep learning, foundation and generative models, representation learning, multimodal methods and LLM-driven tools—to tackle problems across forecasting, market-state estimation, simulation, signal extraction and the research process itself. AI and ML are integrated throughout the research lifecycle.
Strong ideas earn support through evidence. On small teams, researchers can shape the work regardless of seniority and are expected to contribute from the start.
Work alongside researchers, engineers and traders with deep technical and market expertise. Small teams create frequent opportunities to challenge ideas, see how experienced researchers frame problems and strengthen your own technical judgment.
Own meaningful problems across the lifecycle, from deciding what to test through validation and deployment. Technical judgment grows through making those calls, defending the evidence and being accountable for the result.
Researchers, engineers and traders work closely together because the hardest problems require multiple perspectives. Collaboration continues from hypothesis through deployment.
Strong ideas earn support through evidence. On small teams, researchers can shape the work regardless of seniority and are expected to contribute from the start.
Work alongside researchers, engineers and traders with deep technical and market expertise. Small teams create frequent opportunities to challenge ideas, see how experienced researchers frame problems and strengthen your own technical judgment.
Own meaningful problems across the lifecycle, from deciding what to test through validation and deployment. Technical judgment grows through making those calls, defending the evidence and being accountable for the result.
Researchers, engineers and traders work closely together because the hardest problems require multiple perspectives. Collaboration continues from hypothesis through deployment.
We invest in the data, compute, infrastructure and tooling that allow strong research ideas to be tested rigorously and moved into production.
We invest in the data, compute, infrastructure and tooling that allow strong research ideas to be tested rigorously and moved into production.
For students and early-career researchers, development comes through a combination of structured learning, close access to experienced colleagues and meaningful responsibility.
Build judgment by taking on meaningful work early, with fast feedback and increasing responsibility as your capabilities grow.
Managers and teammates provide context, challenge assumptions and help researchers build technical judgment, market understanding and confidence navigating complex problems.
Develop a strong foundation in Quantitative Research, markets and implementation, from statistical modeling and experimentation to writing and testing code that can move into live trading.
For students and early-career researchers, development comes through a combination of structured learning, close access to experienced colleagues and meaningful responsibility.
Build judgment by taking on meaningful work early, with fast feedback and increasing responsibility as your capabilities grow.
Managers and teammates provide context, challenge assumptions and help researchers build technical judgment, market understanding and confidence navigating complex problems.
Develop a strong foundation in Quantitative Research, markets and implementation, from statistical modeling and experimentation to writing and testing code that can move into live trading.
Whether through an internship, full-time role or programs and events students can work on real research problems, learn from experienced colleagues and build an understanding of how Quantitative Research operates in practice.
Whether through an internship, full-time role or programs and events students can work on real research problems, learn from experienced colleagues and build an understanding of how Quantitative Research operates in practice.
Researchers describe the problems they work on, how they collaborate and what has changed in their thinking over their careers at Citadel Securities.
Hear how Yiming applies her passion and resilience to research, working with her teammates to push limits every day.
Researchers describe the problems they work on, how they collaborate and what has changed in their thinking over their careers at Citadel Securities.
Hear how Yiming applies her passion and resilience to research, working with her teammates to push limits every day.
