Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Quantitative Analyst

Sporting Solutions
London
7 months ago
Applications closed

Related Jobs

View all jobs

Baseball Analyst/Data Scientist

Junior Developer/Analyst, Data Science and Analytics - Macquarie Group

Data Scientist/Analyst - NESO

Growth Data Scientist/Analyst

Growth Data Scientist/Analyst

Data Scientist/Analyst - NESO

Job Description

As a member of our QTS team, you will be a key contributor in developing quantitative models and tools required for trading a wide range of sports with an emphasis on using the best possible techniques and technologies to enable continuous improvement of price accuracy, performance and content.


Our Company


Sporting Solutions is one of the world’s leading names in sports betting technology and trading.

The Quantitative Trading Solutions department is one focussed on delivering Trading Models and bespoke Tooling using mathematical expertise and highly skilled software development.

We’re focused on using the best tool for the job so are looking for people who are keen to learn, gain exposure to a wide range of technologies and enjoy working in a continuous and agile delivery environment.


Your main responsibilities are to:


  • Produce logical modelling solutions for business requirements
  • Adapt model features and content in line with business priorities
  • Seeing work through from development to delivery and maintaining accordingly
  • Create statistical and machine learning models to expand and enhance model performance
  • Assist in development of new data driven methodologies
  • Be involved in the verification of proposed changes, especially on derivative effects
  • Clearly expl...

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.

AI Team Structures Explained: Who Does What in a Modern AI Department

Artificial Intelligence (AI) and Machine Learning (ML) are no longer confined to research labs and tech giants. In the UK, organisations from healthcare and finance to retail and logistics are adopting AI to solve problems, automate processes, and create new products. With this growth comes the need for well-structured teams. But what does an AI department actually look like? Who does what? And how do all the moving parts come together to deliver business value? In this guide, we’ll explain modern AI team structures, break down the responsibilities of each role, explore how teams differ in startups versus enterprises, and highlight what UK employers are looking for. Whether you’re an applicant or an employer, this article will help you understand the anatomy of a successful AI department.