At a Glance
- Tasks: Drive advanced modelling to enhance player engagement and growth at PlayStation.
- Company: Join the innovative team at PlayStation, shaping the future of gaming.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with mentorship opportunities and a focus on innovation.
- Why this job: Make a real impact on player experiences using cutting-edge machine learning techniques.
- Qualifications: Proven experience in machine learning, Python, SQL, and strong problem-solving skills.
The predicted salary is between 60000 - 80000 £ per year.
Requirements
- You combine technical depth in machine learning with a proactive, solution-oriented mindset, and the ability to influence strategy and inspire others.
- You thrive on solving sophisticated problems that deepen PlayStation’s understanding of its players and you use this understanding to inform data-driven decisions and strategies that drive player growth.
- Proven industry experience delivering impactful, production-ready machine learning solutions in areas such as customer value, retention, or personalisation.
- Strong expertise in modern machine learning approaches, including applying techniques such as transformers, embeddings, or sequence-based models to real-world behavioural data.
- Ability to critically assess when advanced approaches are warranted versus simpler solutions.
- Experience owning projects end-to-end, including problem definition, navigating ambiguity, selecting modelling approaches, and delivering impactful solutions.
- Ability to work with large, complex datasets and translate them into scalable solutions.
- Strong stakeholder management and communication skills, with the ability to influence decisions and communicate results persuasively to both technical and non-technical audiences.
- Proficiency in Python, SQL, and modern ML tooling (such as Tensorflow, PyTorch, MLlib, feature stores); experience with PySpark or equivalent distributed data processing tools.
- A strong academic background, typically a Master’s or PhD in a technical or quantitative field, specialising in Machine Learning.
- Experience deploying models into production and maintaining business-critical or consumer facing models (Desirable).
- Background in gaming, e-commerce, or subscription-based businesses (Desirable).
- Industry experience with experimentation frameworks and causal inference (Desirable).
- Experience working in agile, fast-paced environments.
What the job involves
- At PlayStation, Data Science plays a critical role in shaping how we invest in, retain, and delight our global player base.
- The CLV & Personalisation 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 Senior Data Scientist, you will drive the development of advanced modelling and analytical approaches that influence key commercial and product decisions at scale and are evaluated based on their impact on commercial outcomes.
- You will work on complex and often ambiguous problems, helping define how we measure player value and how we deliver more personalised player experiences.
- This role combines deep hands-on modelling with ownership of problem definition, approach, and impact.
- You will work with a high degree of autonomy across ambiguous problem spaces, shaping how data informs strategy and decision-making across the business.
- Design and deliver advanced machine learning models to drive player value, engagement, and growth across the lifecycle.
- Own ambiguous problem spaces, defining modelling approaches and breaking down complex business challenges into actionable solutions.
- Partner with senior stakeholders to shape strategies, and ensure Data Science drives high-impact decisions.
- Apply advanced machine learning techniques, including deep learning and sequence modelling, where appropriate to capture complex player behaviours and improve model performance.
- Evaluate and select modelling approaches based on problem context, balancing performance, scalability, and interpretability.
- Work within cross-functional teams, including engineering, product, and commercial stakeholders, to ensure solutions are scalable, production-ready, and aligned with long-term architecture.
- Mentor other data scientists and contribute to best practices across the team.
- Communicate complex modelling approaches, assumptions, and outcomes clearly to senior technical and non-technical audiences.
Senior Data Scientist (CLV & Personalisation) employer: PlayStation
At PlayStation, we pride ourselves on being an exceptional employer that fosters a culture of innovation and collaboration. Our Senior Data Scientists enjoy a dynamic work environment in a vibrant location, with access to cutting-edge technology and the opportunity to influence key strategic decisions that enhance player experiences. We offer robust professional development opportunities, a commitment to work-life balance, and the chance to be part of a passionate team dedicated to pushing the boundaries of gaming through data-driven insights.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist (CLV & Personalisation)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at PlayStation. Use LinkedIn to connect and engage with them. A friendly message can go a long way in getting your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to customer value and personalisation. Share it during interviews or on your LinkedIn profile to impress potential employers.
✨Tip Number 3
Prepare for the interview by brushing up on your technical knowledge. Be ready to discuss your experience with Python, SQL, and ML tools like TensorFlow and PyTorch. Practice explaining complex concepts in simple terms for non-technical audiences.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining the team at PlayStation.
We think you need these skills to ace Senior Data Scientist (CLV & Personalisation)
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your technical expertise in machine learning and data science. We want to see how you've applied advanced techniques like transformers or sequence-based models in real-world scenarios, so don’t hold back!
Be Solution-Oriented:We love a proactive mindset! In your application, share examples of how you've tackled complex problems and influenced strategy. Show us how you’ve turned ambiguity into actionable solutions that drive player engagement.
Tailor Your Application:Don’t just send a generic CV! Tailor your application to reflect the specific requirements of the Senior Data Scientist role. Mention your experience with large datasets and how you've communicated results to both technical and non-technical audiences.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity at PlayStation!
How to prepare for a job interview at PlayStation
✨Know Your Machine Learning Stuff
Make sure you brush up on your machine learning techniques, especially those mentioned in the job description like transformers and sequence-based models. Be ready to discuss how you've applied these in real-world scenarios, particularly in customer value and personalisation.
✨Showcase Your Problem-Solving Skills
Prepare examples of complex problems you've tackled in the past. Highlight your ability to navigate ambiguity and define modelling approaches. This will demonstrate your proactive mindset and solution-oriented approach, which are key for this role.
✨Communicate Like a Pro
Since you'll be working with both technical and non-technical stakeholders, practice explaining your projects and results in simple terms. Use clear examples to show how your work has influenced decisions and strategies, making it relatable to different audiences.
✨Be Ready to Discuss Stakeholder Management
Think about times when you've partnered with senior stakeholders to shape strategies. Be prepared to share how you influenced decisions and ensured that data science drove impactful outcomes. This will highlight your strong communication and management skills.