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- Tasks: Research and implement advanced machine learning techniques in sports analytics.
- Company: Leading sports tech company in Greater London with a focus on innovation.
- Benefits: Mental health support, flexible schedules, and a collaborative work environment.
- Why this job: Join a dynamic team and make an impact in the exciting world of sports analytics.
- Qualifications: Master's or PhD in a related field with 3+ years of experience in Python and SQL.
- Other info: Supportive culture that values diverse thinking and offers career growth.
The predicted salary is between 36000 - 60000 £ per year.
A leading sports tech company based in Greater London is seeking a Data Scientist to join their Machine Learning Modelling team. The role involves researching and implementing advanced machine learning techniques, productizing models, and mentoring team members.
Ideal candidates will have:
- A Master's or PhD in a related field
- 3+ years of experience
- Proficiency in Python and SQL
The company values diverse thinking and offers a supportive work environment, including mental health benefits and flexible schedules.
ML Data Scientist — Sports Analytics & AI employer: Stats Perform
Contact Detail:
Stats Perform Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Data Scientist — Sports Analytics & AI
✨Tip Number 1
Network like a pro! Reach out to people in the sports tech industry on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to sports analytics. 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 Python and SQL skills. Be ready to discuss your past projects and how you've used advanced machine learning techniques to solve real-world problems.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing applications from passionate candidates who are eager to join our team and contribute to innovative projects in sports analytics.
We think you need these skills to ace ML Data Scientist — Sports Analytics & AI
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with Python and SQL in your application. We want to see how you've used these skills in real-world projects, especially in machine learning or data science contexts.
Tailor Your Application: Don’t just send a generic CV and cover letter. Take the time to tailor your application to our job description. Mention specific projects or experiences that relate to sports analytics and AI – we love seeing relevant examples!
Be Yourself: We value diverse thinking, so let your personality shine through in your application. Share your unique perspective on data science and how you approach problem-solving. We’re looking for team players who can bring fresh ideas!
Apply Through Our Website: For the best chance of getting noticed, apply directly through our website. It’s the easiest way for us to keep track of your application and ensures it lands in the right hands. We can’t wait to hear from you!
How to prepare for a job interview at Stats Perform
✨Know Your ML Techniques
Brush up on the latest machine learning techniques relevant to sports analytics. Be ready to discuss how you've applied these methods in your previous roles, and think of specific examples that showcase your problem-solving skills.
✨Showcase Your Coding Skills
Since proficiency in Python and SQL is key, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice coding challenges beforehand to ensure you're comfortable under pressure.
✨Emphasise Team Collaboration
This role involves mentoring and working with others, so highlight your teamwork experiences. Share examples of how you've successfully collaborated with colleagues or mentored junior team members in the past.
✨Align with Company Values
Research the company’s culture and values, especially their focus on diverse thinking and mental health support. Be prepared to discuss how you can contribute to this environment and why it matters to you personally.
