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About the role
- Data Scientist at Hawk-Eye Innovations enhancing officiating, coaching through data analysis. Collaborate with teams to develop data-driven solutions and insights for various sports.
Responsibilities
- Develop and implement sports analytics models and algorithms to support decision-making for teams, coaches, and officials across various sports.
- Analyse large and complex data sets to identify trends, patterns, and insights that can be translated into actionable strategies for performance improvements.
- Collaborate with cross-functional teams, including software engineers, product managers, and other data scientists, to develop and deploy data-driven solutions.
- Create visualisations and reports to communicate insights and findings effectively to technical and non-technical stakeholders.
- Assist in the development and maintenance of internal databases, ensuring data quality and accuracy.
- Contribute to the enhancement of Hawk-Eye's proprietary analytics platforms by continuously refining and optimising their performance and user experience.
- Present findings and insights to clients, partners, and internal teams, ensuring they understand the value and implications of the analytics work being performed.
- Participate in the development and delivery of training materials and workshops to help clients and internal team members better understand and utilize sports analytics tools and techniques.
- Actively contribute to the continuous improvement of Hawk-Eye's analytics processes and methodologies, sharing knowledge and expertise with team members to foster a culture of learning and collaboration.
Requirements
- Bachelor’s degree or equivalent in Data Science, Mathematics, Physical Sciences, Biomechanics, Computer Science or a similar related field.
- Knowledge of sports rules, strategies, and basic statistical concepts.
- Proficiency in Python and experience with data manipulation (e.g. pandas, polars) and visualization tools (e.g. plotly, matplotlib).
- Strong communication and presentation skills.
- Passion for sports and ideally sports analytics, with a desire to continuously learn and stay up-to-date with industry developments.
- Experience with sports data is ideal but not essential.
- Familiarity with sports performance and/or biomechanical data analysis.
- Familiarity with machine learning frameworks and libraries, such as scikit-learn and PyTorch.
- Knowledge of general purpose programming languages such as C++ or Rust.
- Any experience working with large, complex data sets and managing data pipelines, ensuring data quality and integrity.
- Experience in data analysis, predictive modelling, or machine learning, including academic or placement/internship experience.
Benefits
- 25 days annual leave (excluding bank holidays)
- Enhanced pension scheme with 5% matching
- Hybrid working model
- Complimentary Unmind wellbeing app
- Sony Group Company discounts
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