At a Glance
- Tasks: Enhance predictive models and turn insights into production-ready solutions in football analytics.
- Company: Join Football Radar, a leader in football analytics with a start-up vibe and established stability.
- Benefits: Enjoy competitive salary, half-yearly bonuses, 33 days holiday, and flexible working hours.
- Why this job: Make a real impact in sports analytics while collaborating with passionate data scientists.
- Qualifications: STEM degree, knowledge of predictive modelling, and proficiency in Python and SQL.
- Other info: Dynamic environment with opportunities for career growth and innovation.
The predicted salary is between 40000 - 60000 ÂŁ per year.
At Football Radar, our mission is to be the world-leading provider of football analytics. For over a decade, we have combined predictive modelling techniques with expert analysis and our proprietary datasets to deliver insights that drive success for our betting clients and football clubs. By combining the agility of a start-up with the stability of an established business, we’ve created an environment where innovation and long-term success go hand in hand.
As a Data Scientist on our Prediction Team, you will use our extensive dataset to enhance existing predictive models, research new methods, and turn your insights into production‑ready solutions. Your research will involve a mix of well‑executed analyses and innovative modelling to solve unique challenges in football analytics, where your work will directly enhance our predictions and decision‑making processes. To achieve this, you will have the freedom to explore and develop your own ideas while working collaboratively with a team of data scientists, developers, and analysts, to combine technical expertise with football knowledge.
You will be based at our London office, at 106 Kensington High Street, London, W8 4SG. While we are open to flexible working hours to help you avoid rush hour, we believe in the value of in‑person collaboration and learning opportunities, so we require at least 4 days a week in the office.
Requirements
We are looking for smart, ambitious people who are naturally curious, eager to learn, and enjoy solving challenging problems in a dynamic environment. We are open to candidates from early‑career to experienced Data Scientists. The following are the core skills we would expect all candidates to meet:
- A Bachelor’s, Master’s, or PhD in a STEM subject
- Solid understanding of predictive modelling, machine learning, and probability theory
- Familiarity with techniques such as Monte Carlo simulation, Bayesian modelling, mixed effects models, Kalman filters, GLMs, and time series forecasting. While expertise in every area isn’t expected, you should have a broad awareness of available techniques and tools, and understand the trade‑offs of different approaches
- Ability to communicate complex models and analyses clearly to both technical and non‑technical audiences
- Comfort working collaboratively across teams, sharing ideas early, and taking onboard feedback from both technical and football‑focused colleagues
- Proficiency in Python for data analysis and modelling
- Experience working with SQL and relational databases
- Interest in football and sports analytics
For Senior Candidates
More experienced candidates will have the opportunity to take on more responsibility, leading projects, and helping set the direction of our research. We are looking for candidates who can think strategically and make pragmatic decisions about where we should focus our efforts, and what technical approaches we should use to get our modelling ideas onto production. So in addition to the requirements above, this means you also bring:
- 3+ years of experience applying predictive modelling and machine learning in industry, with exposure to sports or betting data through professional work or substantial personal projects
- A practical approach to problem‑solving, balancing attention to detail with the ability to deliver MVPs quickly
- Ability to deliver projects independently, making informed and justifiable decisions, while also contributing effectively as part of a team
- Experience taking models from research into production, and deploying them to the cloud
What We Offer
Half yearly bonus opportunities based on company performance. 33 days holiday (Including...
Data Scientist (Junior or Senior) in London employer: Football Radar
Contact Detail:
Football Radar Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist (Junior or Senior) in London
✨Tip Number 1
Network like a pro! Get out there and connect with people in the football analytics space. Attend meetups, webinars, or even local events. You never know who might have a lead on a job or can give you insider info about Football Radar.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your predictive models and analyses. Use GitHub to share your projects and make sure to highlight any football-related work. This will help us see your passion and expertise in action.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and football knowledge. Be ready to discuss your thought process behind your models and how they can apply to our work at Football Radar. We love candidates who can communicate complex ideas clearly!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows us you’re genuinely interested in joining our team and contributing to our mission in football analytics.
We think you need these skills to ace Data Scientist (Junior or Senior) in London
Some tips for your application 🫡
Show Your Passion for Football Analytics: When you're writing your application, let your love for football and analytics shine through! Mention any relevant projects or experiences that highlight your interest in the field. We want to see that you’re not just a data whiz but also someone who genuinely cares about the game.
Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter for the Data Scientist role at Football Radar. Highlight your skills in predictive modelling and machine learning, and don’t forget to mention any experience with SQL and Python. We appreciate candidates who take the time to align their application with our needs!
Be Clear and Concise: In your written application, clarity is key! Use straightforward language to explain your experiences and skills. Avoid jargon unless it’s necessary, and make sure your points are easy to understand. We want to get to know you without having to decipher complex sentences!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team at Football Radar!
How to prepare for a job interview at Football Radar
✨Know Your Models
Make sure you brush up on your predictive modelling techniques and machine learning concepts. Be ready to discuss how you've applied these in past projects or studies, especially in relation to football analytics. This will show your understanding of the role and your enthusiasm for the subject.
✨Communicate Clearly
Practice explaining complex data science concepts in simple terms. You might be asked to present your ideas to both technical and non-technical audiences, so being able to communicate effectively is key. Use examples from your experience to illustrate your points.
✨Show Your Curiosity
Demonstrate your eagerness to learn and explore new methods. Prepare some questions about Football Radar's current projects or challenges they face in football analytics. This shows that you're not just interested in the job, but also in contributing to their mission.
✨Team Player Mindset
Since collaboration is crucial in this role, think of examples where you've successfully worked in a team. Be ready to discuss how you handle feedback and share ideas with colleagues. Highlighting your ability to work well with others will resonate with their team-oriented culture.