Data Scientist - CLV & Next Best Action

PlayStation Sony Computer Entertainment Europe Ltd.; Camden Town; Hybrid; GBP 100,000 - 125,000; Full time

Job summary

A leading gaming company in Camden Town seeks a Data Scientist to apply modern machine learning techniques to understand and enhance player engagement. The role involves building predictive models, collaborating with multiple teams, and requires strong analytical skills. The ideal candidate should have a Master’s degree in a technical field and proficiency in Python and SQL.

Benefits

Discretionary bonus opportunity

Hybrid Working

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

Qualifications

• Strong analytical and critical thinking skills with a passion for understanding customer behaviour.
• Practical experience with predictive modelling such as churn and value modelling.
• Ability to work with large datasets to uncover actionable insights.

Responsibilities

• Build and validate models for churn prediction and personalised engagement.
• Collaborate with analytics and engineering to ensure efficient models.
• Communicate findings clearly to technical and non-technical partners.

Skills

Machine Learning

Predictive Modelling

Data Analysis

Python

SQL

Education

Master's degree in a technical or mathematical field

Tools

Data Science libraries

Airflow

Tableau

Job description

Overview

Role overview: Our Data Science Analytics and Enablement (DSAE) team inspires PlayStation to make impactful, customer-centric decisions through seamless integration of data. 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. Data Scientists in the DSAE team apply analytical methods to drive value from the data through methods such as customer segmentation, predictive modelling, forecasting and other algorithms. Our work delivers an in-depth understanding of consumer behaviours and supports multi-channel targeting and personalisation. We\'re seeking a motivated and collaborative Data Scientist to join our CLV & Next Best Action / Personalisation team, which builds models that help PlayStation 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 PlayStation\'s Next Best Action and Personalisation strategies. You\'ll help shape how PlayStation 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 PlayStation engages and retains its players.

Responsibilities

• Build and validate models for use cases such as churn prediction, purchase propensity, CLV modelling, and personalised engagement.
• Work with sequential and behavioural data, applying machine learning approaches (e.g., gradient boosting, embeddings, sequence models) to capture player behaviour and growth.
• Partner with commercial, finance, and lifecycle teams to translate business needs into modelling hypotheses that inform engagement strategies.
• Collaborate with analytics and engineering colleagues to ensure models are efficient, robust, and scalable.
• Communicate findings clearly to both technical and non-technical partners, ensuring insights drive measurable outcomes.
• Grow your expertise in modern ML approaches (transformers, representation learning, sequence-to-sequence modelling) through high-visibility projects.
• Strong analytical and critical thinking skills, with a passion for understanding customer behaviour and enabling data-driven growth.
• Practical experience with predictive modelling, such as churn, propensity, segmentation, or value modelling.
• Proficiency in Python and SQL, with fluency in common data science libraries.
• Ability to work with large datasets to uncover actionable insights that influence marketing, engagement, or retention strategies.
• Interest or early experience in deep learning approaches - such as transformers, embeddings, or sequence models - with motivation to learn and apply them.
• A collaborative attitude, with the ability to work in cross-functional teams.
• A strong academic background (typically with a Master\'s in a technical or mathematical field) or equivalent professional experience.

Nice to Have

• Experience with A/B testing or experimentation frameworks.
• Familiarity with workflow orchestration tools (e.g., Airflow), feature stores, or visualisation platforms (e.g., Tableau, Domo).
• Exposure to gaming, e-commerce, or subscription-based business models.
• Proven experience of analysing and modelling with "big data" technologies.
• A personal interest in gaming and entertainment.

Benefits

• 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

Equal Opportunity

Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. PlayStation is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.