Skills

Python Test Research Scikit-Learn Numpy Pandas Analytics Mathematics

Job Specifications

My client is a market-leading organisation operating at the intersection of data analytics, quantitative research, and high-performance modelling. They apply sophisticated statistical and mathematical techniques to develop innovative, data-driven strategies and products within a fast-paced, intellectually challenging environment.

They are now looking for a Quantitative Analyst to join their growing team. This is an excellent opportunity for an experienced quant who enjoys solving complex problems, building rigorous models, and seeing their work deliver measurable real-world results.

Key Responsibilities

Develop and deliver sophisticated mathematical and statistical models aimed at identifying new opportunities and refining existing market strategies.
Utilise strong knowledge of statistical theory, including complex distributions and Monte Carlo techniques, to design and optimise modelling approaches.
Test, validate, and benchmark models to ensure they perform reliably under a range of real-world conditions.
Take ownership of quantitative modelling projects from initial research and prototype design through to full-scale implementation and production.
Present and explain analytical results and model insights clearly to diverse audiences, ensuring transparency and actionable understanding across both technical and commercial stakeholders.

Skills & Experience

Proven experience as a Quantitative Analyst or Modeller, ideally within a similar space, working with sports data.
Track record of successfully developing and delivering impactful quantitative models.
Deep understanding of mathematical and statistical modelling, including complex probability distributions and stochastic methods.
Highly proficient in Python for modelling, data manipulation, and analysis (NumPy, pandas, SciPy, scikit-learn, etc.).

Preferred Qualifications

Advanced degree (MSc or PhD) in a quantitative discipline such as Mathematics, Statistics, Physics, Computer Science, or Engineering.
Experience in sports modelling, market pricing, or other high-frequency modelling environments.

Working Environment

Hybrid working model: 2 days per week in the London office with flexibility for remote work.
Collaborative and research-driven culture, offering exposure to challenging modelling problems and cutting-edge techniques.
Strong focus on innovation, professional development, and high-performance modelling excellence.