At a Glance
- Tasks: Analyse tennis data to generate insights for broadcasters and coaches.
- Company: Join TennisViz, the leader in sports analytics and innovation.
- Benefits: Gain hands-on experience in a fast-growing company with a passion for sports.
- Other info: Opportunity to work with other sports like Cricket and Rugby.
- Why this job: Be at the forefront of sports analytics and make a real impact in the industry.
- Qualifications: Passion for data analysis and knowledge of tennis is a plus.
The predicted salary is between 30000 - 48000 £ per year.
About TennisViz: TennisViz, part of the Ellipse Group, is the world leader in using algorithmic software to process player and ball tracking data to create ground-breaking analysis in real time. Our unique automated software captures every shot, situation, phase, and tactic, which are the foundation of a new set of performance metrics called TennisViz Insights.
With ambitious plans for growth, we are looking to recruit a Junior Data Scientist to join us at the cutting edge of sports analytics. This is a unique opportunity to be part of the growth story of our rapidly expanding business.
Responsibilities:
- You will be working with experienced tennis analysts, using a very extensive tennis database consisting of match results, official point-by-point data and ball/player tracking data etc. from all levels of the professional game.
- You will be analysing and interpreting granular tracking data to generate new insights on player performances for use by clients such as broadcasters and professional coaches.
- You may also have the opportunity to work on other sports in the business such as Cricket, Rugby.
Junior Data Scientist - TennisViz employer: Ellipse
Ellipse is an exceptional employer that fosters a vibrant and inclusive work culture, where innovation thrives and personal development is prioritised. Located in Kennington, London, our hybrid working model allows for flexibility while engaging with a passionate team dedicated to revolutionising sports performance data. With comprehensive training opportunities, a supportive Employee Assistance Programme, and a commitment to diversity, we empower our employees to grow and excel in their careers.
StudySmarter Expert Advice🤫
We think this is how you could land Junior Data Scientist - TennisViz
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Ellipse!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Junior Data Scientist - TennisViz at Ellipse.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Ellipse.
✨Apply Directly through Our Website
When you find a suitable opening like Junior Data Scientist - TennisViz at Ellipse, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Junior Data Scientist - TennisViz
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Ellipse, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Ellipse. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Ellipse
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Ellipse!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
