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Quantitative Researcher
Job in
London, Greater London, W1B, England, UK
Listed on 2026-09-03
Listing for:
Venture Up
Full Time
position Listed on 2026-09-03
Job specializations:
-
Business
Data Scientist
Job Description & How to Apply Below
Skills:
Python stack (numpy, pandas etc.), R, Tensor Flow.
* Please note this role cannot sponsor. Please do not apply if you are seeking sponsorship
* Job Summary Quantitative Researcher is required for exciting and progressive Sports betting Hedge fund Company with office in London and Leeds. You will be developing statistical models to compute the probabilities of outcomes in various sports. Sports modelling is their core expertise and the company is structuring the company around creating the best possible technical and cultural environment to enable you to rapidly explore and test alternative models.
You will join a highly skilled and experienced team answering a variety of complex sporting questions. You will work on building probabilistic models, the quality and evolution of which are central to the company’s success. You will find innovative ways of extracting information from various sporting and market data sources. Modelling and predicting sports outcomes is a uniquely challenging field, and you will have plenty of opportunities to use your experience, judgement and imagination to solve difficult problems.
As Quantitative Researcher you will need:
· 1+ years experience
· Statistics graduate/post-graduate
· Electronic Trading Experience
· Python, Tensor Flow
· Straight As at A level (or equivalent)
· Kaggle profile (or other practical statistical experience)
The Opportunity
· Opportunities to progress your quantitative developer career.
· Working in GLMs, BMMs, Kalman filters, MCMC and the True Skill Ranking system
· Working with some of the brightest Quants within the industry.
Job Information Industry Financial Services Date Opened 03/01/2024 Job Type Full time Tech Stack Python Work Experience 1-3 years City London State/Province Greater London Country United Kingdom Zip/Postal Code EC1A
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