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bet3651 day ago

Lead Data Scientist, Sports

Hybrid · Manchester, England, United Kingdom

Type
Full Time
Level
Mid Level
Education
Masters Degree
Company size
Enterprise

Job Summary

Lead Data Scientist to spearhead development of advanced probabilistic models powering real-time betting markets. Develop models to determine odds and power in-play betting decisions using state-of-the-art machine learning techniques; collaborate across quantitative analysis, trading, and software teams; mentor junior colleagues; leverage Python/R and ML frameworks; deploy scalable models in cloud environments; drive data-driven insights aligned with business objectives.

Required Qualifications

  • Master’s degree or PhD in Mathematics, Data Science, Computer Science, or a related quantitative field.
  • Proven success in leading the design, development, and deployment of sophisticated predictive models.
  • Expertise in Python/R and ML frameworks, such as scikit-learn, TensorFlow, or PyTorch
  • Proven ability to design and implement complex machine learning solutions and guiding best practice.
  • Deep understanding of statistical analysis and probability theory.
  • Demonstrable experience overseeing the implementation of highly accurate, computationally efficient, and scalable models for large-scale production environments.
  • Track record of mentoring junior colleagues and successfully leading technical projects.
  • Experience with cloud computing environments for scalable solutions.
  • Leading the development and implementation of innovative data solutions for complex challenges, solving problems without prescriptive approaches.
  • Overseeing advanced analysis of large datasets to derive actionable insights aligned with business objectives.
  • Developing predictive models and algorithms using statistical techniques and machine learning.
  • Conducting and supervising rigorous statistical validation of models against historical and live data.
  • Collaborating with trading teams to incorporate domain expertise into mathematical models.
  • Partnering with software architects and developers to ensure alignment with technical solutions.
  • Optimising model performance for both accuracy and computational efficiency.
  • Researching and implementing novel approaches from academic literature and industry advancements.
  • Mentoring less experienced team members, providing guidance, and conducting quality assurance to enhance overall team performance and capabilities.
  • Identifying and defining new opportunities for data-driven insights.
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Lead Data Scientist, Sports

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