Company:
Harnham
Location: London
Closing Date: 29/10/2024
Hours: Full Time
Type: Permanent
Job Requirements / Description
Job Description
SENIOR DATA SCIENTIST - SPORTS PERFORMANCE ANALYTICS
Up to £90,000 + Bonus
LONDON
Ready to elevate your career to new heights? Join our team of experienced Data Scientists and Data Engineers to create impactful models and work with cutting-edge technologies. We aim to become the world's leading provider of performance analytics software in the sports industry, leveraging Machine Learning to optimize athlete performance and team strategies.
The Role:
Your day-to-day responsibilities will include:
- Deploying Data Science projects that directly impact sports performance and team success.
- Building Machine Learning algorithms and models using Python to develop innovative performance analytics tools for athletes and coaches.
- Coding and testing new algorithms for prototype and production applications using Python libraries like TensorFlow and Keras, with a focus on sports-related data.
- Translating complex sports data into meaningful insights using Python, helping teams make data-driven decisions.
- Taking the lead in interacting with sports professionals, coaches, and stakeholders to showcase the project.
Your Skills and Experience:
- MSc or PhD level education in STEM subjects, with a strong focus on sports analytics or a related field.
- Proven expertise in implementing Machine Learning and clustering techniques specifically tailored to sports performance.
- Strong commercial experience with Python and data visualization, along with proficient knowledge of Python, R, and Scala, with an emphasis on sports data.
- Previous commercial exposure to tools such as Keras, TensorFlow, Python, specifically in the context of sports performance analytics.
- Excellent communication skills and ability to engage with teams, coaches, and sports professionals.
Benefits:
- Competitive salary range of £80,000 - £90,000.
- Outstanding career progression opportunities.
- Flexible working arrangements.
How to Apply:
Register your interest by sending your CV to Luc Simpson-Kent, via the link.
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