Senior Data Scientist - CLV & Next Best Action
What You'll Be Doing:
- Design and deliver models that quantify player value, engagement, and growth, shaping strategies across the player lifecycle.
- Apply advanced ML and deep learning approaches (e.g., transformers, embeddings, sequence models) to capture player behaviours and monetisation patterns.
- Partner with senior stakeholders in commercial, finance, and lifecycle teams to define roadmaps and ensure CLV and Next Best Action modelling advises high-impact decisions.
- Translate sophisticated, ambiguous business needs into modelling strategies that guide engagement and growth.
- Work with engineering partners to ensure solutions are robust, scalable, and production-ready.
- Mentor colleagues and influence best practices, fostering technical growth and knowledge sharing across the team.
- Communicate modelling rationale, assumptions, and results persuasively to technical and non-technical senior audiences.
- Proven experience building predictive models for customer value, engagement, retention, or monetisation.
- Expertise in modern ML and deep learning techniques, including transformers, embeddings, and sequence models for behavioural or transactional data.
- Ability to work with large-scale, complex datasets to generate actionable insights and scalable models.
- Proficiency in Python, PySpark, and SQL, with fluency in common ML libraries and experience building robust modelling pipelines.
- A track record of shaping modelling strategies and ensuring solutions are impactful, scalable, and production-ready.
- Excellent communication skills, with the ability to explain concepts persuasively to senior business leaders.
- A collaborative, empowering approach, with experience mentoring colleagues and contributing to team-wide innovation.
- A strong academic background (typically a Master's or PhD in a technical or quantitative field) or equivalent professional experience.
- Experience with workflow orchestration tools (e.g., Airflow), feature stores, or visualisation platforms (e.g., Tableau, Domo).
- Proven experience in gaming, e-commerce, or subscription-based business models.
- Experience deploying ML models in production environments and working with MLOps tools.
- A personal interest in gaming and entertainment.
- Discretionary bonus opportunity
- Hybrid Working (within Flexmodes)
- Private Medical Insurance
- Dental Scheme
- 25 days holiday per year
- On Site Gym
- Subsidised Café
- Free soft drinks
- On site bar
- Access to cycle garage and showers
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