Junior Data Scientist - TennisViz

Ellipse
London
3 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst / Junior Data Scientist

Junior Data Analyst

Junior Data Analyst

Junior Data Analyst - Power BI / SQL

Graduate Data Analyst

Trainee Data Analyst Excel, SQL & Power BI)

About TennisViz:

 

TennisViz, part of the Ellipse Group, is the world leader in using algorithmic software to process player and ball tracking data to create ground-breaking analysis in real time. Our unique automated software captures every shot, situation, phase, and tactic, which are the foundation of a new set of performance metrics called TennisViz Insights.

 

Job Description

 

With ambitious plans for growth, we are looking to recruit a Junior Data Scientist to join us at the cutting edge of sports analytics.


This is a unique opportunity to be part of the growth story of our rapidly expanding business.


Responsibilities:


● You will be working with experienced tennis analysts, using a very extensive tennis database consisting of match results, official point-by-point data and ball/player tracking data etc. from all levels of the professional game.

● You will be analysing and interpreting granular tracking data to generate new insights on player performances for use by clients such as broadcasters and professional coaches.

● You may also have the opportunity to work on other sports in the business such as Cricket, Rugby & Horse Racing.


Requirements:


● Strong interest and knowledge in a variety of sports, in particular tennis.

● Experience with the PyData stack (pandas, numpy, scikit-learn, matplotlib etc.).

● Knowledge of machine learning and statistical models, e.g. linear/logistic regression, decision trees, random forest, unsupervised methods etc.

● Basic knowledge of relational databases and SQL.

● Experience conveying complex information through Data Visualisation.


Nice to have:


● Experience working with sports data.

● Understanding of version control systems like Git.

● Comfortable working with the command line.

 

 

Equality & diversity

Ellipse is committed to building an open and inclusive culture that supports personal development and learning. Ellipse believes in the principle of equal opportunity in employment and its employment policies for recruitment, training, development and promotion despite any differences based on individual grounds of race, colour, nationality, religion or belief, sex, sexual orientation, marital status, age, ethnic and national origin, disability or gender reassignment.


Benefits


● 25 days’ holiday plus bank holidays

● Hybrid role with an expectation to work from our new offices in London and Leeds when required

● Company pension scheme

● Company life insurance

● Flexible Employee Benefits


About Ellipse:


TennisViz is part of Ellipse. Ellipse is a leading sports data and analytics company comprising CricViz, FootballViz, Horse Racing, RugbyViz (Oval and Stuart Farmer Media Services) and TennisViz. Working with the world’s biggest broadcasters, professional teams and rights holders, we simplify complex data to engage a broad and diverse audience and tell better stories about the sports we love.


Please apply using this link: https://ellipsedata.com/jobs/junior-data-scientist/


*We cannot promise to respond to all applicans due to the volume we receive

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.