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A leading sports analytics company in London is looking for a Machine Learning Researcher to enhance their predictive modeling capabilities. You will design, test, and implement machine learning models in Python, with significant autonomy to explore innovative solutions. Ideal candidates will have a strong quantitative background, preferably with a Master's or PhD, and experience in competitive modeling projects. Benefits include a bonus scheme, matched pension contributions, and private healthcare.
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At Longshot Systems we're building advanced platforms for sports betting analytics and trading.
We're hiring Machine Learning Researchers for our quantitative modelling team. The primary goal of this team is to improve the predictive power of our models based on historical event and market data. The quality of our models is incredibly important to us and improvements on our models directly impact company success.
You will design, test, and implement new machine learning models in Python, continually improving our existing state-of-the-art solutions. Longshot is a small, focused company and so the role suits someone who wants to be involved in all aspects of the R&D process, from high-level design through to production implementation.
The ideal candidate will be highly creative and enjoy generating new, innovative ways to tackle problems and suggesting improvements to existing methodologies; you'll have a high level of autonomy to research whichever methods you felt would be best suited to the problem at hand. A strong mathematical understanding of the fundamentals of Machine Learning and core statistics is very important for this role. Sports betting knowledge isn't required, though experience modelling sports - especially in-play football, basketball, or tennis - is helpful.
We are a hybrid working company, working Thursdays in our London (Farringdon) office and flexible the rest of the week. Our typical working hours are 10 am to 6 pm UK time, Monday to Friday, but we support flexible working and trust our team to manage their own schedules to meet their goals.
Our interview process is as follows:
At least one of:
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.