
Data Science Manager
- London
- Permanent
- Full-time
- Take ownership of our Commercial Data Science team and its roadmap.
- Lead a team of Data Scientists and Machine Learning Engineers across a variety of projects from conception to delivery.
- Work closely with stakeholders to align our deliveries with company-wide goals.
- Support senior management in defining the vision for our state-of-the-art Data Science functions, with a strong emphasis in automated insights, machine learning & AI driven decisioning.
- Foster a culture of high performance, excellence and innovation across our many initiatives.
- Line management, coaching, and professional development of team members, identifying skill gaps and proactively addressing them, ensuring continuous skill development.
- Keeping your team engaged, motivated, and supported.
- Maintain strong relationships and communication at the interfaces of our domain, namely with our business owners and engineering teams.
- Contribute to building a culture of excellence within the wider Automation & Insights department and beyond by aligning tools, best practice, process, and governance.
- Raise the profile of the team by actively promoting work and team contributions across the organization.
- Recruitment of further team members, ensuring alignment with your team's evolving skill requirements.
- Bachelor's or advanced degree in a STEM subject.
- Experience managing a team of Data Scientists/Machine Learning Engineers developing machine learning data products. Ability to engage, motivate, and empathise with individuals.
- In-depth understanding and experience building machine learning/AI algorithms and solutions from conceptions to production.
- Advanced knowledge of machine learning algorithms, and statistics.
- Advanced knowledge of A/B testing and design of experiment.
- Exemplary Python and SQL skills, experience using Spark for processing large datasets.
- Familiarity with cloud computing platforms, preferably experience with Amazon Web Services.
- Understanding of software product development processes and governance, including CI/CD processes, release and change management.
- Understanding of machine learning product lifecycle, and how scientists and engineers collaborate in cross-functional product teams.
- Understanding of ML deployment paradigms including batch, event driven, and request-response.
- Knowledge of gitops processes for testing and deployment, e.g. Jenkins and Terraform. Strong awareness of software development best practices.
- Passionate about the personal development of self and team members.
- Interest and understanding of product domains, from online gaming to sportsbook.
- Excellent interpersonal skills, able to explain complex concepts to stakeholders.
- A problem-solving growth mindset with the ability to pick up new concepts quickly.