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Hunter Bond

Senior Machine Learning Researcher : Elite Quant Fund : £300-400k+

London
£300k – £400k/yr
Posted 1 day ago
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About the Role

A leading quantitative investment fund is seeking to appoint a Senior Machine Learning Researcher to join and further develop its Machine Learning Research function. The team is focused on applying advanced machine learning research to quantitative investment and financial markets.

Responsibilities

The successful candidate will have the opportunity to work on challenging, open-ended research problems at the intersection of machine learning, large-scale data, and quantitative finance, with access to significant computational and research resources. Candidates should have a strong understanding of the underlying principles of modern machine learning and a demonstrated ability to conduct rigorous, independent research.

The team is particularly interested in researchers with strong expertise in one or more of the following areas:

  • Diffusion models and generative modelling
  • Transformer architectures and foundation models
  • Computer vision and visual representation learning
  • Deep learning
  • Self-supervised and representation learning
  • Large-scale model development and training
  • Novel neural network architectures and modelling techniques

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Requirements

The preferred candidate will have experience in machine learning research, applied research, or a closely related discipline. The fund places particular value on depth of industry research experience and demonstrated technical capability.

Candidates are expected to demonstrate:

  • A strong academic background in machine learning, computer science, mathematics, physics, or a related quantitative discipline
  • A Master's degree from a leading university or equivalent academic institution
  • Significant industry experience in machine learning research
  • Demonstrable expertise in diffusion models, transformers, computer vision, or related areas
  • Strong mathematical and statistical foundations
  • Experience developing, evaluating, and implementing novel machine learning approaches
  • The ability to formulate and investigate open-ended research questions independently
  • A high level of technical proficiency and intellectual curiosity

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Opportunities

The successful candidate will join a high-calibre research environment and will be expected to make a significant contribution to the development of the firm's machine learning capabilities. There is substantial scope for the successful researcher to:

  • Define and pursue new research directions
  • Develop novel machine learning methodologies for application to financial data
  • Collaborate closely with quantitative researchers and other machine learning specialists
  • Access significant computational and research resources
  • Contribute to the development of the firm's broader machine learning research strategy
  • Build and lead a dedicated research team as the function expands
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Skills

Diffusion Models
Generative Modelling
Transformer Architectures
Foundation Models
Computer Vision
Deep Learning
Self-supervised Learning
Representation Learning
Large-scale Model Training
Neural Network Architectures
Quantitative Finance
Mathematical Foundations
Statistical Foundations
Machine Learning Research
Financial Data Analysis

Location

London, England, United Kingdom

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