At a Glance
- Tasks: Create algorithms and derive insights from athlete performance data to enhance training.
- Company: Join Hudl, a top-rated workplace dedicated to sports innovation.
- Benefits: Enjoy flexible work options, competitive salary, and professional development opportunities.
- Other info: Collaborative culture with a focus on work-life balance and career growth.
- Why this job: Make a real impact on athletes' performance while working with cutting-edge technology.
- Qualifications: Strong background in mathematics and experience with AI/ML models required.
The predicted salary is between 60000 - 80000 € per year.
At Hudl, we build great teams. We hire the best of the best to ensure you’re working with people you can constantly learn from. You’re trusted to get your work done your way while testing the limits of what’s possible and what’s next. We work hard to provide a culture where everyone feels supported, and our employees feel it—their votes helped us become one of Newsweek's Top 100 Global Most Loved Workplaces. We think of ourselves as the team behind the team, supporting the lifelong impact sports can have: the lessons in teamwork and dedication; the influence of inspiring coaches; and the opportunities to reach new heights. That’s why we help teams from all over the world see their game differently. Our products make it easier for coaches and athletes at any level to capture video, analyze data, share highlights and more.
Your Role
We're hiring a Senior Data Scientist to join our Athlete Performance team in London. You'll be partnering with world class sports scientists and engineering teams to build algorithms and derive insights from wearable sensors, optical tracking and GPS data that directly impact how athletes train and compete, from local high schools to professional teams. For this role, we're currently considering candidates who live within a commuting distance of our offices in London or Barcelona.
Responsibilities
- Create and improve algorithms. You'll use your expertise in signal processing to run mathematical and statistical operations on raw sensor and GPS data. Your work will help us derive high‑value metrics around human movement classification and physical load quantification, turning raw data into actionable insights for our users.
- Deliver insights at scale. You'll build and deploy models that provide contextualized data to sports scientists, coaches and recruiters.
- Collaborate across teams. You'll work closely with internal product and engineering teams to integrate optical tracking and wearable data, ensuring our products meet the highest standards.
- Lead high‑impact projects. You'll own initiatives that meet quarterly goals and help shape the future of athlete performance tracking at Hudl.
Must‑Haves
- Strong mathematical background. You're highly skilled in statistical operations and physics‑based calculations used to analyze large datasets.
- Proven track record. You've built, maintained and monitored complex AI or ML models in a production environment at scale. You have experience with model observability and managing data drift to ensure long‑term performance. You're also comfortable with CI/CD for ML (like MLflow or TFX) and know how to write effective unit tests for stochastic processes. You have a background in biomechanical modeling and signal processing.
- Multi‑modal time series expertise. You have demonstrable experience working with multi‑modal time series data for deep learning‑based analysis and forecasting, and can apply these techniques to derive meaningful insights from complex sensor data streams.
- Product‑focused. You understand how to translate raw data into actionable insights that solve real problems for coaches and athletes.
Nice‑to‑Haves
- Wearable and GPS expertise. You have experience working with wearable devices, IMU sensors, GPS tracking and biometric data.
- Subject matter expertise. You have a deep understanding of biomechanics or exercise physiology and know how to apply these domains to create meaningful performance insights for athletes.
- Knowledge of foundational models. You have experience fine‑tuning visual or large language models for new domains.
- Real‑time systems experience. You're comfortable working with models designed for low‑latency environments.
- Advanced degree. A PhD in biometrics, mathematics or a related field is a plus.
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 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
The base salary range for this role is displayed below—starting salaries will typically fall near the middle of this range. Our compensation decisions are based on an individual's experience, skills and education in line with our internal pay equity practices. This role will also be eligible for a long‑term incentive (LTI) award.
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. We also know imposter syndrome is real and the confidence gap can get in the way of meeting spectacular candidates. Please don’t hesitate to apply—we’d love to hear from you.
Senior Data Scientist - Athlete Performance Barcelona, Spain; London, United Kingdom employer: Hudl
At Hudl, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to excel. With a strong emphasis on professional development, flexible work arrangements, and a commitment to employee wellbeing, we ensure that our team members in Barcelona and London can thrive both personally and professionally. Join us to collaborate with top-tier sports scientists and engineers, while making a meaningful impact on athlete performance worldwide.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist - Athlete Performance Barcelona, Spain; London, United Kingdom
✨Tip Number 1
Network like a pro! Reach out to people in the industry, 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! If you've got a portfolio or any projects related to data science, make sure to highlight them during interviews. Real-world examples can really set you apart from the crowd.
✨Tip Number 3
Prepare for the technical stuff! Brush up on your algorithms and statistical methods. Be ready to discuss how you've tackled complex problems in the past—this is your chance to shine!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining the Hudl team.
We think you need these skills to ace Senior Data Scientist - Athlete Performance Barcelona, Spain; London, United Kingdom
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Data Scientist role. Highlight your experience with algorithms, data analysis, and any relevant projects that showcase your skills in signal processing and multi-modal time series data.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about athlete performance and how your background aligns with our mission at Hudl. Don’t forget to mention specific experiences that demonstrate your expertise.
Showcase Your Projects:If you've worked on any relevant projects, make sure to include them in your application. Whether it's a personal project or something from your previous job, showing off your hands-on experience with AI/ML models can really set you apart.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to see your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Hudl
✨Know Your Algorithms
Brush up on your algorithm knowledge, especially those related to signal processing and multi-modal time series data. Be ready to discuss specific algorithms you've created or improved in the past, and how they impacted athlete performance.
✨Showcase Your Collaboration Skills
Since you'll be working closely with sports scientists and engineering teams, prepare examples of successful collaborations from your previous roles. Highlight how you integrated different data sources and worked towards common goals.
✨Prepare for Technical Questions
Expect technical questions about AI/ML models, data drift management, and CI/CD processes. Brush up on your knowledge of tools like MLflow or TFX, and be ready to explain how you've applied these in real-world scenarios.
✨Understand the Product Focus
Familiarise yourself with Hudl's products and how they help coaches and athletes. Think about how your skills can translate raw data into actionable insights that solve real problems, and be prepared to discuss this during the interview.