🕒 5 days ago
Research and engineer latent-reasoning methods for tabular foundation models, evaluating their accuracy, calibration, and robustness while using interpretability techniques to analyze model computations.
Graduate Machine Learning Researcher
🕒 13 days ago
Machine LearningPythonTabular Data ModellingQuantitative Modelling
📜 Description
- Design, test, and implement machine learning models in Python.
- Improve existing models that predict outcomes from historical event data.
- Contribute across the R&D process, from high-level design to production implementation.
- Research and propose methods to address modelling problems and improve existing methodologies.
🛠️ Requirements
- PhD or research Masters in a quantitative, technical subject (e.g. Maths, Physics, Machine Learning) from a top university
- Experience modelling tabular data in Python
✨ Benefits
- Participation in the uncapped company bonus scheme, typically 10-20% of salary depending on experience
- 10% matched pension contributions
- Private healthcare insurance
- Long term illness insurance
- Gym membership
- Choose your own hardware & setup for your development environment
Full job description
At Longshot Systems we're building advanced platforms for sports betting analytics and trading.
We're hiring Graduate 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 data. The quality of our models is incredibly important to us and improvements to 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 and who has a keenness to learn from experienced industry experts.
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 feel 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. Knowledge of sports betting isn't required.
We are a hybrid working company, working Thursdays in our London (Farringdon) office and remotely 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:
- Intro call (30 mins) - your background + interests
- Technical interview (60 mins) - modelling discussion + scenario questions
- Full assessment day (10:00–17:00) - solving a real modelling problem using near-production-level data
Requirements
- PhD or research Masters in a quantitative, technical subject (e.g. Maths, Physics, Machine Learning) from a top university
- Experience modelling tabular data in Python
Benefits
- Participation in the uncapped company bonus scheme, typically 10-20% of salary depending on experience
- 10% matched pension contributions
- Private healthcare insurance
- Long term illness insurance
- Gym membership
- Choose your own hardware & setup for your development environment
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