At a Glance
- Tasks: Lead the development of innovative football analytics and machine learning models.
- Company: Join Hudl, a leader in sports technology with a collaborative culture.
- Benefits: Enjoy flexible working, professional growth support, and wellbeing resources.
- Other info: Mentor team members and thrive in a dynamic, inclusive environment.
- Why this job: Make a real impact in football analytics and work with industry-leading data.
- Qualifications: Strong background in quantitative disciplines and experience in statistical modelling.
The predicted salary is between 60000 - 80000 € per year.
Hudl are seeking a Lead Data Scientist to join their Global Football Metrics team, driving the development of cutting‑edge machine learning models and football analytics products used across the professional game. This role offers the opportunity to work with industry‑leading football data, delivering tactical and recruitment insights through advanced statistical modelling and scalable data solutions.
Key Responsibilities
- Lead research and development of new football models and metrics
- Build statistical and machine learning solutions using large‑scale football datasets
- Collaborate cross‑functionally with Engineering, Product, QA, and Design teams
- Contribute to scalable data pipelines, orchestration, and monitoring tools
- Mentor team members and promote best practices in statistical rigour and development
- Deliver innovative tactical and recruitment insights for real‑world application
Essential Requirements
- Strong background in a quantitative discipline
- Proven experience developing statistical and machine learning models
- Strong problem‑solving and collaborative mindset
- User‑focused approach with interest in applied analytics
- Willingness to learn and contribute across technical areas
Desirable
- Experience with football event or tracking data
- Knowledge of Python, PostgreSQL, and Redshift
- Experience with R or Stan considered beneficial
What Hudl Offer
- Flexible & remote working options
- Professional development and career growth support
- Wellbeing resources and employee support programmes
- Modern office spaces and remote working technology
- Inclusive, collaborative working culture
An outstanding opportunity to work at the forefront of football analytics with one of the world’s leading sports technology companies.
Lead Data Scientist – Global Football Metrics | Hudl employer: TheASPA
Hudl is an exceptional employer, offering a dynamic and inclusive work culture that fosters collaboration and innovation in the field of football analytics. With flexible working options, robust professional development support, and a commitment to employee wellbeing, Hudl empowers its team members to thrive both personally and professionally while contributing to cutting-edge projects in sports technology.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Scientist – Global Football Metrics | Hudl
✨Tip Number 1
Network like a pro! Reach out to people in the football analytics space, especially those at Hudl. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning models or any football analytics projects you've worked on. This is your chance to shine and demonstrate your expertise beyond the CV.
✨Tip Number 3
Prepare for the interview by brushing up on your problem-solving skills. Be ready to tackle real-world scenarios related to football data. We want to see how you think and approach challenges!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you're genuinely interested in joining the Hudl team.
We think you need these skills to ace Lead Data Scientist – Global Football Metrics | Hudl
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Lead Data Scientist role. Highlight your experience with statistical and machine learning models, especially if you've worked with football data. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about football analytics and how your background makes you a great fit for our team. We love seeing enthusiasm and a user-focused approach.
Showcase Your Projects:If you've worked on relevant projects, whether in a professional or personal capacity, make sure to mention them. We’re interested in your problem-solving skills and how you've applied analytics in real-world scenarios, so don’t hold back!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to showcase your application in the best light. Plus, we love seeing applications come directly from our site!
How to prepare for a job interview at TheASPA
✨Know Your Data
Make sure you brush up on your knowledge of football data and analytics. Familiarise yourself with the types of datasets Hudl uses and think about how you can apply machine learning models to derive insights from them. Being able to discuss specific examples will show your passion and expertise.
✨Showcase Your Problem-Solving Skills
Prepare to discuss past projects where you've tackled complex problems using statistical methods or machine learning. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This will demonstrate your strong problem-solving mindset that Hudl values.
✨Collaborate Like a Pro
Since this role involves cross-functional collaboration, think of examples where you've worked with different teams. Highlight your ability to communicate effectively with engineers, product managers, and designers. This will show that you can thrive in a collaborative environment, which is key at Hudl.
✨Embrace Continuous Learning
Hudl appreciates a willingness to learn, so be prepared to discuss how you stay updated with the latest trends in data science and football analytics. Mention any courses, workshops, or personal projects that showcase your commitment to professional development and your user-focused approach.
