Machine Learning Researcher, Options

At Citadel Securities, we are at a once-in-a-generation opportunity in the financial markets. Machine Learning Researchers on our Options team turn cutting-edge ideas and petabyte-scale data into bleeding edge models with direct trading impact. Our team of researchers iterate quickly, own decisions end-to-end, and operate with substantial autonomy, resources, and scope in a flat, no-bureaucracy environment.

Opportunities may be available from time to time in any location in which the business is based for suitable candidates. If you are interested in a career with Citadel, please share your details and we will contact you if there is a vacancy available.

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• Own the full research lifecycle, from hypothesis, experiment design, model validation, risk/overfit controls, to deployment
  
• Ship models to production that move P\&L in options markets—measured by clear, testable outcomes
  
• Prototype → test → iterate fast. The resources and support to take great ideas from concept to trading in a very short space of time
  
• Discover alpha in high-dimensional data with deep learning, time-series, and representation learning
  
• Engineer scalable research pipelines from feature generation to distributed training and backtesting
  
• Develop trading intuition to translate insights into executable strategies
  
• Leverage large scale compute and data (petabytes; large budgets) to run ambitious experiments and push the frontier
  

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• Masters or PhD degree in mathematics, statistics, physics, computer science, or another highly quantitative field
  
• Advanced training and strong research track record in statistics, machine learning, AI, or another highly quantitative field
  
• A results-oriented track record of having taken ML ideas from theory to measurable impact
  
• Strong math fundamentals (linear algebra, probability, optimization) and mastery of regression/ML for large scale data
  
• Fluency in Python (NumPy, PyTorch) and the ability to write clean, modular, performant code for large-scale experiments
  
• Hands-on with modern machine learning (sequence models/transformers, representation learning, regularization, cross-validation, causal/robust inference) applied in practice
  
• Bias to action & problem-solving demonstrated ability and comfort around owning decisions, iterating quickly, and simplifying complex problems to impactful solutions
  
• Curiosity about markets and enthusiasm to learn microstructure, options dynamics, and volatility regimes on the job
  

Citadel

Senior (5+ years of experience)