If you share our love of sports and tech, you've got the passion and will to better the sports-tech and data industries – join the team!
Responsibilities:
Team Leadership: Lead and mentor a team of data scientists, ML engineers, and data analysts, fostering a culture of collaboration, innovation, and continuous improvement.
Project Management: Oversee the planning, execution, and delivery of data science and machine learning projects, ensuring alignment with business goals and timelines.
Model Development: Guide the team in developing, testing, and deploying predictive models, machine learning algorithms, and AI solutions.
Data Strategy: Collaborate with stakeholders to define data strategies, identify opportunities for leveraging data to drive business solutions, and ensure the quality and availability of data for analysis.
Technical Expertise: Stay up-to-date with the latest advancements in data science, machine learning, and AI, and apply this knowledge to enhance the teams technical capabilities.
Cross-functional Collaboration: Work closely with other departments, including Engineering, Product, and Marketing, to ensure the integration of ML models into business processes and products.
Performance Monitoring: Establish key performance indicators (KPIs) for model accuracy, efficiency, and scalability, and implement strategies for continuous improvement.
Resource Management: Manage team resources, including tools, software, and data infrastructure, to optimize productivity and performance.
Reporting: Provide regular updates to senior management on the status of projects, team performance, and insights derived from data analysis.
At least 5 years of experience in data science, machine learning, or related fields, with at least 2 years in a leadership role.
Proficiency in programming languages such as Python or R.
Experience with machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn.
Familiarity with data processing tools (e.g., SQL, Spark), cloud platforms (e.g., AWS, GCP), and version control systems (e.g., Git).
Bachelors or Masters degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. A Ph.D. is an advantage.
Strong analytical and problem-solving skills, with experience in statistical analysis, data mining, and predictive modeling.
Proven ability to lead, mentor, and develop high-performing teams, with excellent communication and interpersonal skills.
Vast understanding of how to translate business problems into data-driven solutions, with a focus on delivering measurable impact.
