Senior Data Scientist – CLV & Action

Why Play Station?

Play Station isn’t just the Best Place to Play — it’s also the Best Place to Work. Today, we’re recognized as a global leader in entertainment producing The Play Station family of products and services including Play Station®5, Play Station®4, Play Station®VR, Play Station®Plus, acclaimed Play Station software titles from Play Station Studios, and more.

Play Station also strives to create an inclusive environment that empowers employees and embraces diversity. We welcome and encourage everyone who has a passion and curiosity for innovation, technology, and play to explore our open positions and join our growing global team.

The Play Station brand falls under Sony Interactive Entertainment, a wholly-owned subsidiary of Sony Group Corporation.

Our Data Science Analytics and Enablement (DSAE) team inspires Play Station to make impactful, customer-centric decisions through seamless integration of data.

Currently there are over 100 people in the global DSAE team, including data science, data governance and analytics professionals. We work closely with engineering and product management teams to deliver data products, insight, predictive analytics, and data visualisation.

We’re seeking an experienced and collaborative Senior Data Scientist to join our CLV & Next Best Action / Personalisation team
, which builds models that help Play Station understand and influence the value, growth, and engagement of our global player base.

By connecting player behaviours to long‑term outcomes, our work creates the intelligence that underpins Customer Lifetime Value (CLV) modelling and guides Play Station’s Next Best Action and Personalisation strategies. You’ll help shape how Play Station invests in, retains, and delights its players – and advance our use of modern machine learning at global scale.

This is an exciting opportunity to develop your skills in modern machine learning while contributing to high‑impact projects that directly influence how Play Station engages and retains its players.

• 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.

You combine technical depth in machine learning with the ability to influence strategy and inspire others. You thrive on solving sophisticated problems that deepen Play Station’s understanding of its players and you use this understanding to drive decision and growth strategies related to player growth.

• 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…