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- Tasks: Analyse tennis tracking data to provide insights for coaches and broadcasters.
- Company: Leading sports data analytics company with an innovative team.
- Benefits: Hybrid work model, exposure to multiple sports, and professional development opportunities.
- Why this job: Combine your passion for sports with data science to make a real impact.
- Qualifications: Strong interest in sports, experience with the PyData stack, and machine learning knowledge.
- Other info: Dynamic environment with opportunities to work on various sports analytics projects.
The predicted salary is between 28800 - 48000 £ per year.
A leading sports data analytics company is looking for a Junior Data Scientist to join their innovative team. This role involves analyzing extensive tennis tracking data to generate insights for clients such as professional coaches and broadcasters.
Ideal candidates will have:
- a strong interest in sports
- experience with the PyData stack
- knowledge of machine learning
The position offers a hybrid work model, allowing exposure to multiple sports, including cricket and rugby.
Hybrid Junior Data Scientist - Sports Analytics & Insights employer: Ellipsedata
Contact Detail:
Ellipsedata Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Hybrid Junior Data Scientist - Sports Analytics & Insights
✨Tip Number 1
Network like a pro! Reach out to people in the sports analytics field on LinkedIn or at local meetups. We can’t stress enough how valuable personal connections can be in landing that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data analysis projects, especially those related to sports. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of the PyData stack and machine learning concepts. We recommend practising common interview questions and even doing mock interviews with friends.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing passionate candidates who are eager to join our innovative team.
We think you need these skills to ace Hybrid Junior Data Scientist - Sports Analytics & Insights
Some tips for your application 🫡
Show Your Passion for Sports: When writing your application, let your love for sports shine through! Mention any relevant experiences or projects that showcase your interest in sports analytics. We want to see how your enthusiasm aligns with our mission.
Highlight Your Technical Skills: Make sure to emphasise your experience with the PyData stack and any machine learning knowledge you have. We’re looking for candidates who can hit the ground running, so don’t hold back on showcasing your technical prowess!
Tailor Your Application: Don’t just send a generic application! Take the time to tailor your CV and cover letter to the Junior Data Scientist role. Mention specific skills and experiences that relate directly to the job description. We appreciate when candidates take this extra step!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications better and ensures you don’t miss out on any important updates. Plus, it’s super easy to do!
How to prepare for a job interview at Ellipsedata
✨Know Your Data
Make sure you brush up on your knowledge of the PyData stack. Be ready to discuss how you've used libraries like Pandas, NumPy, and Matplotlib in past projects. Showing that you can manipulate and analyse data effectively will impress the interviewers.
✨Show Your Passion for Sports
Since this role is all about sports analytics, demonstrate your enthusiasm for sports, especially tennis, cricket, and rugby. Share any personal experiences or insights you've gained from following these sports, as it will help you connect with the team and show that you're genuinely interested in the field.
✨Prepare for Machine Learning Questions
Brush up on your machine learning concepts and be prepared to discuss algorithms you've worked with. Think about how you can apply these techniques to sports data. Being able to explain your thought process and how you approach problem-solving will set you apart.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the types of projects you'll be working on or how the team collaborates on data analysis. This shows your interest in the role and helps you gauge if it's the right fit for you.
