AI/ML Quant Specialist - Selby Jennings

A leading proprietary trading firm is seeking an exceptionalAI/ML Specialist to join its research team. This role sits at the intersection ofmachine learning, statistics, probability and quantitative research, applying advanced modelling techniques to complex problems within financial markets.

The successful candidate will combine strong ML expertise with exceptional mathematical foundations and a rigorous approach to experimentation. You will work alongside quantitative researchers, traders and engineers to develop innovative models and extract meaningful signals from large, noisy datasets.

• Research and develop advancedmachine learning and statistical models for quantitative and trading applications.
• Apply techniques fromstatistics, probability, deep learning and probabilistic modelling to complex real-world problems.
• Develop predictive models using large-scale, high-dimensional and noisy datasets.
• Explore new approaches across areas such astime-series modelling, representation learning, reinforcement learning, Bayesian methods and generative modelling.
• Design rigorous experiments to evaluate model performance, robustness and generalisation.
• Work closely with quantitative researchers and traders to identify areas where ML can improve research and decision-making.
• Develop scalable research workflows and collaborate with engineers to move successful models towards production.
• Stay current with developments across machine learning, statistics and AI, assessing their applicability to quantitative trading.
• Contribute to a highly collaborative, research-driven environment where ideas are tested quickly and objectively.

We are looking for candidates with exceptional technical and mathematical ability, particularly acrossmachine learning, statistics and probability.

The ideal candidate will have:

• Strong expertise in modern machine learning and statistical modelling.
• Excellent foundations inprobability theory, statistics, linear algebra and optimisation.
• Experience developing sophisticated predictive or probabilistic models.
• Strong understanding of experimental design, statistical validation and model generalisation.
• Experience working with large, complex or noisy datasets.
• Strong programming ability, particularly inPython.
• Experience with ML frameworks such asPyTorch, JAX or TensorFlow.
• Ability to approach open-ended research problems with mathematical and scientific rigour.
• Strong communication skills and the ability to collaborate with researchers, traders and engineers.

Experience in several of the following would be particularly valuable:

• Statistical Learning
• Probability & Stochastic Modelling
• Bayesian Inference
• Deep Learning
• Time-Series Modelling
• Representation Learning
• Reinforcement Learning
• Generative Models
• Optimisation
• Monte Carlo Methods
• PyTorch / JAX
• Python
• Large-scale data analysis

Candidates donot need experience across every area. Exceptional depth in machine learning combined with particularly strongstatistics and probability skills is more important.

A strong academic background in a highly quantitative discipline is preferred, including:

• Machine Learning / Artificial Intelligence
• Statistics
• Mathematics
• Computer Science
• Physics
• Electrical Engineering
• Operations Research

AMaster's or PhD from a strong academic institution would be highly attractive, particularly where the candidate has undertaken research involving advanced machine learning, statistics or probabilistic modelling.

This is an opportunity to work in an environment wheremathematical rigour, machine learning and real-world impact are closely connected.

You will have access to challenging datasets, strong computational resources and highly technical colleagues, with the freedom to explore sophisticated research ideas and apply them to some of the most difficult quantitative problems in financial markets.