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Quantitative Analyst

Oakwell Hampton
London
1 year ago
Applications closed

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Data Scientist, Quantitative Strategies (Asset & Wealth Management)

Quantitative Analyst (Multiple positions available)

Location:North London (Hybrid – 1 day per week in-office, with flexibility)

Salary:£55,000-£100,000+ and Benefits & Bonus

Sponsorship is Available



Skills, Experience, Qualifications, If you have the right match for this opportunity, then make sure to apply today.

Join a forward-thinking organisation renowned for delivering world-class predictive models and innovative software across global sports. This is an opportunity to apply your quantitative expertise in a fast-paced environment where your models can directly impact real-world outcomes in a range of sports including football (soccer), American Football, baseball, basketball, and more.


A pioneer in data-driven research, collaborating with experts to push the boundaries of sports analytics and betting strategies.


Key Responsibilities:

  • Design and develop predictive models for one or more US or Global sports
  • Collaborate with execution teams to research and deploy automated betting algorithms for market exchanges, owning your models from concept to deployment.
  • Contribute to research discussions, enhancing existing models and identifying new opportunities for improvement.
  • Mentor junior analysts, offering guidance and constructive feedback to enhance their development.
  • Maintain and develop the software infrastructure that powers predictive models and mathematical tools.

Skills & Experience:

  • MSc in mathematics, computer science, or a related field.
  • PhD or equivalent experience of 2+ years in a similar quantitative role.
  • Programming skills in Python, R, C++, or Julia.
  • Expertise in probabilistic and statistical modelling, Bayesian models, or machine learning techniques.
  • Experience with automated trading systems, deep learning, reinforcement learning, or dynamic optimisation.
  • Ability to clearly communicate complex results to both technical and non-technical stakeholders.


Nice to have but not essential:

  • Passion for sports like football, American football, baseball, basketball, cricket, tennis, or ice hockey.
  • Strong foundation in computational statistics, feature engineering, and optimal control techniques.


This role offers a unique chance to shape the future of sports analytics, with the autonomy to bring your ideas to life and see immediate results in a high-stakes, fast-feedback environment.

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