Location
London (Farringdon) office on Thursdays, remote work the rest of the week (hybrid working)

Hours
Typically 10 am to 6 pm UK time, Monday to Friday. Flexible working supported with trust to manage your own schedule to meet goals.

Salary
Competitive salary (details not specified)

About the Role
At Longshot Systems Ltd, we are building advanced platforms for sports betting analytics and trading. We are seeking Graduate Machine Learning Researchers to join our quantitative modelling team. The primary goal is to enhance the predictive power of our models using historical event data. The quality of our models is crucial and improvements directly impact company success. You will design, test, and implement new machine learning models in Python, continually refining our state-of-the-art solutions.
Longshot is a small, focused company, ideal for someone who wants involvement in all aspects of the R&D process—from high-level design through to production implementation. You will have the opportunity to learn from experienced industry experts and enjoy a high level of autonomy to research and apply innovative methods best suited to the problems at hand.
The role requires creativity, a passion for problem-solving, and the ability to suggest improvements to existing methodologies. A strong mathematical understanding of machine learning fundamentals and core statistics is essential. Knowledge of sports betting is not required.
Our interview process includes an introductory call, a technical interview focused on modelling and scenario questions, and a full assessment day solving a real modelling problem using near-production-level data.

Experience
PhD or research Masters in a quantitative, technical subject such as Maths, Physics, or Machine Learning from a top university.
Experience modelling tabular data in Python.

About you
Highly creative and motivated to generate innovative solutions.
Enjoys working autonomously and collaboratively in a small, focused team.
Keen to learn from experienced industry experts.
Strong mathematical and statistical understanding relevant to machine learning.

Qualifications
PhD or research Masters degree in a relevant quantitative or technical field.