Machine Learning Researcher, Options

Role Overview

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.

Responsibilities

• 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

Skills and Preferred Qualifications

• 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

Company

Citadel

Senior (5+ years of experience)