Graduate Machine Learning Researcher

Dubizzle Limited; City of London; Hybrid; GBP 30,000 - 40,000; Full time

Job summary

A leading sports analytics firm in London is seeking a Graduate Machine Learning Researcher to enhance predictive modeling in sports betting analytics. You will design and implement innovative machine learning models using Python. Candidates should have strong mathematical skills and a background in quantitative research, with opportunities for creative input and research autonomy. This role offers a hybrid work model with competitive benefits including a bonus scheme and matched pension contributions.

Benefits

Uncapped company bonus scheme

10% matched pension contributions

Private healthcare insurance

Long term illness insurance

Gym membership

Choose your own hardware & setup

Qualifications

• Strong mathematical understanding of the fundamentals of Machine Learning.
• Experience modelling tabular data in Python.

Responsibilities

• Design, test, and implement new machine learning models.
• Improve existing state-of-the-art solutions.
• Participate in R&D process from design to implementation.

Skills

Machine Learning

Python

Mathematics

Problem Solving

Education

PhD or research Masters in a quantitative, technical subject

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 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 and 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 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. 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 (9:30–5pm) - solving a real modelling problem using near-production-level data

• 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

• 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