HG
Machine Learning Researcher
Accepting applicationsHWTS Global · New York, United States
Full-Time Mid_senior Machine LearningPythonatedeep learningmachine learning
Posted
20 Apr
Category
Eda
Experience
Mid_senior
Country
United States
Machine Learning Researcher | London / New York | Leading Quantitative Investment Platform
We’re working with a globally recognised, data-driven investment firm looking to hire a Machine Learning Researcher to join a highly academic, research-focused team. The group operates at the intersection of advanced ML and real-world decision systems, applying cutting-edge techniques to large-scale, complex datasets.
Notably, prior financial experience is not required — this team is actively seeking individuals from academic or research-heavy backgrounds who can bring fresh thinking and rigorous methodology.
What You’ll Be Doing
Conduct original machine learning research with direct real-world application
Develop and implement state-of-the-art models across large, high-dimensional datasets
Explore areas such as deep learning, NLP, reinforcement learning, and LLMs
Work closely with a collaborative team of researchers and engineers to translate theory into production
Contribute to a culture of experimentation, publication-level research, and continuous innovation
Core Requirements
PhD (preferred) or MSc from a leading university in a quantitative field (e.g. Machine Learning, Computer Science, Mathematics, Physics, Statistics)
Strong track record in machine learning research (academic or industry), including publications or impactful projects
Advanced Python programming skills and experience with ML frameworks (e.g. PyTorch, TensorFlow)
Deep understanding of modern ML techniques (e.g. deep learning, probabilistic models, optimisation)
Strong grounding in statistics, linear algebra, and algorithm design
Ability to work on open-ended problems and translate research ideas into practical solutions
Nice to Have
Experience working with large-scale or noisy real-world datasets
Familiarity with distributed computing or high-performance systems
Exposure to LLMs, generative models, or reinforcement learning
Background in competitive programming, research competitions, or top-tier conferences
Why This Role
Opportunity to work in a pure research-driven environment with real-world impact
No requirement for financial experience — strong academic talent is the priority
Access to world-class data, infrastructure, and compute
Collaborative, intellectually rigorous culture alongside top-tier researchers
Flexibility across London or New York offices
If you’re coming from a strong ML research background and want to apply your work in a high-impact, real-world setting, feel free to reach out for a confidential discussion.
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We’re working with a globally recognised, data-driven investment firm looking to hire a Machine Learning Researcher to join a highly academic, research-focused team. The group operates at the intersection of advanced ML and real-world decision systems, applying cutting-edge techniques to large-scale, complex datasets.
Notably, prior financial experience is not required — this team is actively seeking individuals from academic or research-heavy backgrounds who can bring fresh thinking and rigorous methodology.
What You’ll Be Doing
Conduct original machine learning research with direct real-world application
Develop and implement state-of-the-art models across large, high-dimensional datasets
Explore areas such as deep learning, NLP, reinforcement learning, and LLMs
Work closely with a collaborative team of researchers and engineers to translate theory into production
Contribute to a culture of experimentation, publication-level research, and continuous innovation
Core Requirements
PhD (preferred) or MSc from a leading university in a quantitative field (e.g. Machine Learning, Computer Science, Mathematics, Physics, Statistics)
Strong track record in machine learning research (academic or industry), including publications or impactful projects
Advanced Python programming skills and experience with ML frameworks (e.g. PyTorch, TensorFlow)
Deep understanding of modern ML techniques (e.g. deep learning, probabilistic models, optimisation)
Strong grounding in statistics, linear algebra, and algorithm design
Ability to work on open-ended problems and translate research ideas into practical solutions
Nice to Have
Experience working with large-scale or noisy real-world datasets
Familiarity with distributed computing or high-performance systems
Exposure to LLMs, generative models, or reinforcement learning
Background in competitive programming, research competitions, or top-tier conferences
Why This Role
Opportunity to work in a pure research-driven environment with real-world impact
No requirement for financial experience — strong academic talent is the priority
Access to world-class data, infrastructure, and compute
Collaborative, intellectually rigorous culture alongside top-tier researchers
Flexibility across London or New York offices
If you’re coming from a strong ML research background and want to apply your work in a high-impact, real-world setting, feel free to reach out for a confidential discussion.
Show more Show less