At a Glance
- Tasks: Develop algorithms to analyse data from wearable sensors and GPS for athlete performance.
- Company: Hudl, a leader in sports technology with a focus on innovation.
- Benefits: Remote work options, professional development, and a supportive work-life balance.
- Other info: Join a collaborative team dedicated to enhancing athletic performance.
- Why this job: Make a real impact on athletes' performance using cutting-edge data science techniques.
- Qualifications: Strong mathematical skills and experience with AI/ML models required.
The predicted salary is between 60000 - 80000 € per year.
Hudl is seeking a Senior Data Scientist to join their Athlete Performance team in London. In this role, you will develop and improve algorithms using signal processing techniques to analyze data from wearable sensors and GPS, assisting athletes across various competitive levels.
The ideal candidate will have:
- a strong mathematical background,
- experience with AI/ML models,
- the ability to work with multi-modal time series data.
Hudl supports work-life harmony and values professional development in a collaborative environment.
Senior Data Scientist, Athlete Performance (Remote Options) in London employer: Hudl
Hudl is an exceptional employer that champions work-life harmony and fosters a collaborative culture, making it an ideal place for a Senior Data Scientist to thrive. With a strong emphasis on professional development, employees are encouraged to grow their skills while contributing to innovative projects that enhance athlete performance. The London location offers a vibrant atmosphere, providing unique opportunities to engage with a diverse team dedicated to pushing the boundaries of sports technology.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist, Athlete Performance (Remote Options) in London
✨Tip Number 1
Network like a pro! Reach out to current or former Hudl employees on LinkedIn. A friendly chat can give us insider info about the company culture and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your work with AI/ML models and signal processing techniques. This will help us stand out during interviews and demonstrate our expertise.
✨Tip Number 3
Practice makes perfect! Mock interviews with friends or mentors can help us refine our answers and boost our confidence. Focus on explaining complex concepts in simple terms, especially around multi-modal time series data.
✨Tip Number 4
Apply through our website! It’s the best way to ensure our application gets noticed. Plus, we can tailor our application to highlight how our skills align with Hudl's mission in athlete performance.
We think you need these skills to ace Senior Data Scientist, Athlete Performance (Remote Options) in London
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your mathematical background and experience with AI/ML models in your application. We want to see how your skills can help us develop and improve algorithms for athlete performance.
Be Specific About Your Experience:When discussing your past projects, focus on your work with multi-modal time series data and signal processing techniques. We love details that show how you've tackled similar challenges before!
Tailor Your Application:Don’t just send a generic CV and cover letter. Tailor your application to reflect our values of collaboration and professional development. Show us why you’re a great fit for our team at Hudl!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Hudl
✨Brush Up on Your Maths Skills
Since the role requires a strong mathematical background, make sure you’re comfortable with concepts like statistics, linear algebra, and calculus. Be prepared to discuss how you've applied these skills in previous projects or roles.
✨Showcase Your AI/ML Experience
Highlight your experience with AI and machine learning models during the interview. Bring examples of projects where you've developed or improved algorithms, especially those related to signal processing or time series data.
✨Understand Multi-Modal Data
Familiarise yourself with multi-modal time series data and be ready to discuss how you’ve worked with different types of data sources. This will demonstrate your ability to handle the complexities of the role and show that you can think critically about data integration.
✨Emphasise Collaboration and Development
Hudl values a collaborative environment, so be sure to share experiences where you’ve worked effectively in teams. Discuss how you’ve contributed to professional development, both for yourself and your colleagues, to align with their work-life harmony ethos.
