Data Scientist - Forecasting

sonyinteractiveentertainmentglobal; Greater London; On-site; GBP 65,000 - 90,000; Full time

Benefits offered by this job

Discretionary bonus

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

Job summary

Sony Interactive Entertainment in the United Kingdom is seeking a Data Scientist to develop models and insights that drive personalised player experiences and inform commercial and product decisions at scale. You will translate player behaviour into actionable strategies and work across engineering, product, and commercial teams to deliver measurable improvements in engagement and value.

You should be comfortable owning problems end-to-end, from framing to delivery, and be able to communicate

Qualifications

• Experience building predictive models in a commercial setting.
• Ability to independently take a problem from definition through to solution and delivery.
• Proficiency in Python and SQL.
• Solid understanding of machine learning techniques and when to apply them.
• Strong communication and collaboration skills.
• Awareness of modern machine learning approaches and how to apply them.
• Experience working with large datasets to generate actionable insights.
• Strong academic background in a quantitative or technical field (Master’s or Ph.D.).

Responsibilities

• Own the development and delivery of machine learning models for churn, purchase propensity, store recommendations, and CLV.
• Translate business problems into modelling approaches and features.
• Work with large-scale behavioural and transactional data to uncover patterns and opportunities for player growth and engagement.
• Collaborate within cross-functional teams to ensure robust, scalable solutions aligned with business needs.
• Partner with stakeholders across commercial, finance, and lifecycle teams to support data-driven decisions.
• Clearly communicate findings and recommendations to technical and non-technical audiences.
• Develop and expand understanding of advanced modelling approaches (deep learning and sequence-based methods).

Skills

Predictive modelling

Problem ownership

Python

SQL

ML techniques

Communication

Embeddings/Deep learning

Big data

Advanced degree

Education

Master’s or Ph.D. in a quantitative field

Tools

PySpark

Job description

Why Sony Interactive Entertainment?

Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity.

Department overview:

At PlayStation, Data Science plays a critical role in shaping how we invest in, retain, and delight our global player base. The CLV team focuses on understanding player behaviour and driving more effective engagement across the player lifecycle — from acquisition and onboarding through to retention, monetisation, and long-term value.

As a Data Scientist, you will develop models and insights that help drive more personalised player experiences and inform commercial and product decisions at scale. You will work in cross-functional teams to translate player behaviour into actionable strategies that drive measurable improvements in player engagement and value.

This role is ideal for an individual who is comfortable owning problems end-to-end — from framing and modelling through to delivering impact — and partnering with stakeholders to support data-informed decision-making.

What you’ll be doing:

• Own the development and delivery of machine learning models for use cases such as churn prediction, purchase propensity, store recommendations, customer lifetime value.
• Translate business problems into modelling approaches, selecting appropriate methods and features to deliver measurable impact.
• Work with large-scale behavioural and transactional data to uncover patterns and opportunities for player growth and engagement.
• Collaborate within cross-functional teams, including engineering, product, and commercial stakeholders, to ensure solutions are robust, scalable, and aligned with business needs.
• Partner with stakeholders across commercial, finance, and lifecycle teams to support decision-making with data-driven insights.
• Clearly communicate findings and recommendations to both technical and non-technical audiences.
• Develop and expand your understanding of more advanced modelling approaches (e.g. deep learning and sequence-based methods) as part of solving increasingly complex problems.

What we are looking for:

You’re curious, analytical, and a strong problem-solver, with a structured approach to tackling business problems. You bring strong foundations in modelling and data manipulation, and are motivated by applying these to impactful, commercial problems.

• Experience building predictive models (e.g. churn, propensity, segmentation, or value modelling) in a commercial setting.
• Ability to independently take a problem from definition through to solution and delivery, demonstrating initiative and ownership.
• Proficiency in Python and SQL, and familiarity with common data science and ML libraries.
• Solid understanding of machine learning techniques (e.g. regression, tree-based models, clustering) and when to apply them, including how to refine and tune them for real-world problems.
• Strong communication and collaboration skills, with the ability to clearly articulate insights and work effectively with cross-functional stakeholders.
• Awareness of modern machine learning approaches (e.g. embeddings, sequence models, deep learning) and interest in applying them to real-world problems.
• Experience working with large datasets to generate actionable insights.
• A strong academic background, typically a Master’s or Ph.D. in a quantitative or technical field (e.g. Mathematics, Statistics, Computer Science).

Nice to Have:

• Familiarity with production environments, MLOps, or data pipelines.
• Experience working with large-scale data using PySpark or equivalent distributed data processing tools.
• Experience in gaming, e-commerce, or subscription-based products.

Benefits:

• Discretionary bonus opportunity
• 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

Please refer to our Candidate Privacy Notice for more information about how we process your personal information, and your data protection rights.

Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks.

Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights.

Equal Opportunity Statement:

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.

Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

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