Data Scientist

Ludonautics
City of London
2 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist - Supply Chain Optimisation

About Ludonautics


Ludonautics is a sports advisory business dedicated to helping sporting organisations make data-informed decisions through access to insightful statistical analysis. Ludonautics was founded in 2023 by Ian Graham, who previously served as Liverpool FC's Director of Research for 11 years.


What will you be doing?


Ludonautics needs a full-stack Data Scientist who will work closely with engineering and client-facing staff to ship dependable data tooling and models. The successful applicant will develop tools and pipelines to support analysis and to build and deploy models to automated production workflows.


Who are we looking for?


We are looking for a data scientist who is comfortable with Python and SQL, and with learning new skills and technologies. The successful candidate will have experience developing and deploying statistical models.


We expect the successful candidate to be able to document the merits of different approaches to a problem from a high-level model requirements specification, and to be able to implement and integrate a performant, robust, and scalable solution in a production environment with minimal supervision.


This is primarily a remote role, with frequent in-person co-working days (2-3 days every 4-6 weeks), usually in London.


Skills and Experience:


Desired experience:

  • Master's degree in a STEM field, or equivalent experience in technical/analytical roles
  • Python
  • SQL
  • Statistical modelling
  • Data engineering fundamentals


Responsibilities:

  • Engineer and deliver new models and tools that run reliably and repeatably
  • Translate ideas into clear analytical requirements and production‑ready tools and models
  • Build and maintain analysis pipelines and tooling that reduce manual effort for the client team
  • Collaborate with engineers to develop and deploy models and integrate outputs into automated workflows


Benefits


  • Competitive salary
  • Remote working
  • Flexible hours
  • Holiday buyback scheme
  • Pension Contributions
  • Bonus scheme based on the success of our clients and of the company


Equal Opportunity


We welcome applicants of all backgrounds and identities


Contact


Please apply via LinkedIn - No Agencies

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.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.