At a Glance
- Tasks: Lead innovative machine learning projects in sports analytics with a dynamic team.
- Company: Join Hudl, a leader in sports technology and analytics.
- Benefits: Enjoy flexible work options, competitive salary, and professional growth opportunities.
- Other info: Flexible work-life balance and a supportive, inclusive culture.
- Why this job: Make a real impact in sports by developing cutting-edge data models.
- Qualifications: Strong background in quantitative disciplines and experience with statistical models.
The predicted salary is between 76000 - 127000 € per year.
We’re looking for a Lead Data Scientist to join our Global Football Metrics data science team, which is focused on delivering innovative machine learning models to keep Hudl at the cutting edge of sports analytics.
Your Role
- Work with a cross‑functional team. You’ll collaborate with Engineering, Quality Assurance, Product, Design and Scrum disciplines to deliver cutting‑edge tactical and recruitment insights.
- Develop and deliver. You will have access to industry‑leading data from a variety of sources, and will lead the research and development roadmap for new Global Football models and metrics.
- Test new ideas. At Hudl, we iterate rapidly, deploying changes to the product hundreds of times daily across our Engineering team. In addition to working on concrete metrics, you’ll contribute to the implementation of scalable data pipelines and associated orchestration and monitoring tools.
- Mentor. You’ll share your expertise and educate others on development best practices and trade‑offs, setting an example in planning, designing and delivering complex projects, and maintaining high standards of statistical rigour.
We’d like to hire someone for this role who lives near our office in London, but we’re also open to remote candidates. Remote candidates would have the ability to work from a co‑working space or their home.
Must‑Haves
- Technical expertise. You have a strong background in a quantitative discipline, and proven experience implementing statistical and machine learning models for statistical inference in complex systems.
- A team player. You understand that problem‑solving is a team effort and will help others on our Engineering team learn and develop their skills.
- User‑focused. You’re excited to have your work used by real people to solve real problems.
- Willing to learn. You have solid engineering skills but are always willing to dive into specific areas to gain the expertise needed to be successful in your role.
Nice‑to‑Haves
- Sports industry experience. If you’ve worked with event or tracking data previously, that’s a plus.
- Tech stack knowledge. Our tech stack is Python, PostgreSQL and Redshift. We will consider strong candidates with experience of R or Stan, but prefer those with more full stack skills and capable of writing production code.
Our Role
- Champion work‑life harmony. We’ll give you the flexibility you need in your work life (e.g., flexible vacation time above any required statutory leave, company‑wide holidays and timeout (meeting‑free) days, remote work options and more) so you can enjoy your personal life too.
- Guarantee autonomy. We have an open, honest culture and we trust our people from day one. Your team will support you, but you’ll own your work and have the agency to try new ideas.
- Encourage career growth. We’re lifelong learners who encourage professional development. We’ll give you tons of resources and opportunities to keep growing.
- Provide an environment to help you succeed. We've invested in our offices, designing incredible spaces with our employees in mind. But whether you’re at the office or working remotely, we’ll provide you the tech you need to do your best work.
- Support your wellbeing. Depending on location, we offer medical and retirement benefits for employees—but no matter where you’re located, we have resources like our Employee Assistance Program and employee resource groups to support your mental health.
Compensation
Base Salary Range: £76,000 - £127,000 GBP. This role will also be eligible for a long‑term incentive (LTI) award. Our compensation decisions are based on an individual's experience, skills and education in line with our internal pay equity practices.
Inclusion at Hudl
Hudl is an equal opportunity employer. Through our actions, behaviors and attitude, we’ll create an environment where everyone, no matter their differences, feels like they belong. We offer resources to ensure our employees feel safe bringing their authentic selves to work, including employee resource groups and communities. But we recognize there’s ongoing work to be done, which is why we track our efforts and commitments in annual inclusion reports.
Lead Data Scientist — Global Football Metrics employer: Hudl
Hudl is an exceptional employer that champions work-life harmony and offers a flexible environment, allowing you to thrive both personally and professionally. With a strong focus on career growth, you'll have access to extensive resources and opportunities for development, all while collaborating with a talented cross-functional team in the vibrant city of London or remotely. Our commitment to inclusivity and employee wellbeing ensures that every team member feels valued and supported, making Hudl a truly rewarding place to work.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Scientist — Global Football Metrics
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Hudl or similar companies. 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 and data projects. This is your chance to shine and demonstrate how you can contribute to the Global Football Metrics team.
✨Tip Number 3
Prepare for the interview by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your past experiences and how they relate to the role. We want to see your passion for sports analytics!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining our team at Hudl. Let’s get you on board!
We think you need these skills to ace Lead Data Scientist — Global Football Metrics
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Lead Data Scientist role. Highlight your experience with machine learning models and any relevant projects you've worked on. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're excited about the role and how your background makes you a perfect fit for our Global Football Metrics team. Let your passion for sports analytics come through!
Showcase Team Collaboration:Since we value teamwork, share examples of how you've collaborated with cross-functional teams in the past. Whether it's working with engineers or product designers, we want to know how you contribute to a team environment.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Hudl
✨Know Your Data Science Stuff
Make sure you brush up on your machine learning models and statistical methods. Be ready to discuss specific projects where you've implemented these techniques, especially in complex systems. This will show that you have the technical expertise they’re looking for.
✨Show Off Your Team Spirit
Since collaboration is key in this role, think of examples where you've worked effectively in a team. Highlight how you’ve helped others learn and grow, as well as how you’ve contributed to problem-solving as a group. This will demonstrate that you’re a true team player.
✨Get Familiar with Their Tech Stack
If you have experience with Python, PostgreSQL, or Redshift, make sure to mention it! If not, do some quick research to understand these technologies. Being able to speak their language will definitely give you an edge during the interview.
✨Be Ready to Discuss Real-World Applications
Prepare to talk about how your work has impacted real users. Think of specific examples where your data insights led to tangible results. This will show that you’re user-focused and excited about solving real problems, which is exactly what they want.