Skills

Python Test Decision-making Research Training Architecture Machine Learning PyTorch TensorFlow Deep Learning Programming C++ Mathematics

Job Specifications

A highly sophisticated technology-driven investment firm is building out a next-generation research team focused on applying modern machine learning to complex prediction problems across global financial markets.

This position sits at the intersection of fundamental research and real-world impact. You will develop novel modelling approaches, work with extremely large and high-fidelity datasets, and help translate research insights into production systems that influence automated decision-making at scale.

Key Responsibilities

Develop and evaluate advanced machine learning models for prediction, pattern discovery, and signal generation
Explore deep learning architectures across structured and unstructured data sources
Design large-scale experimentation pipelines to test hypotheses and measure model robustness
Partner with quantitative researchers and engineers to move research prototypes into production environments
Improve model performance through feature innovation, architecture exploration, and optimization strategies
Build research tooling and infrastructure that accelerates iteration and experimentation
Analyze complex time-dependent datasets to uncover relationships relevant to market behavior

Ideal Background

Doctorate in a quantitative discipline such as Machine Learning, Computer Science, Statistics, Mathematics, or Physics
Meaningful experience developing and deploying deep learning models in research or industry settings
Demonstrated intellectual contribution to the field through publications, open research, or impactful systems
Strong programming ability in Python or C++
Experience working with modern ML ecosystems such as PyTorch, JAX, or TensorFlow
Exposure to sequence modelling, time-series forecasting, reinforcement learning, or probabilistic modelling
Strong mathematical intuition combined with practical engineering instincts
Ability to operate in highly collaborative, performance-driven technical environments

What Makes This Opportunity Compelling

Direct influence on real-time automated decision systems
Access to significant computational resources and uniquely rich datasets
Close collaboration with elite technical peers across research and engineering
Fast research-to-production feedback cycles
Compensation structure designed to attract top global ML talent

Base salary: Approximately $300K, with final compensation based on role scope, experience, education and training, and key skills.

Visa sponsorship is available for this position.

About the Company

Oscar Faye is a high-performance talent solutions firm operating at the crossroads of human capability and technological acceleration. We find the people who create tomorrow. They are the builders, researchers and operators shaping what the world will be capable of next. We specialise in talent-scarce, complexity-heavy markets where many claim expertise but few truly understand the terrain. This is where our experience makes the difference. Our backgrounds lie at the forefront of innovative technology and finance and our... Know more