Staff Data Scientist – Experimentation: Innovation & Research United Kingdom, London

PlayStation
City of London
3 weeks ago
Create job alert

United Kingdom, London

Why PlayStation?

PlayStation 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 PlayStation family of products and services including PlayStation®5, PlayStation®4, PlayStation®VR, PlayStation®Plus, acclaimed PlayStation software titles from PlayStation Studios, and more.

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

As a Staff Data Scientist, you will lead innovation in experimentation and causal inference, helping shape the future of decision-making and product innovation at SIE. You will drive innovative research in experimentation methodologies while mentoring other team members. You’ll be responsible for elevating our experimentation strategy, fostering a culture of curiosity and rigor, and helping cross-functional teams deliver player-first experiences through strong evidence-based decisions.

What You’ll Be Doing:
  • Drive innovation in experimentation research by shaping measurement frameworks and best practices, and by developing new methodologies that enhance the quality, speed, and scalability of experiments.
  • Advance experimentation infrastructure and tooling, incorporating statistical and machine learning methods to refine analytical capabilities.
  • Mentor and guide less-senior data scientists, building expertise in experimentation and causal inference while providing technical direction to ensure rigor and impact.
  • Partner with product managers and business leaders to identify high-impact experimentation opportunities and align them with PlayStation’s strategic goals.
  • Act as a thought leader in experimentation and causal inference, evangelizing best practices and fostering learning across teams.
  • Contribute to research and prototyping of novel experimentation techniques that address complex real-world challenges, such as user behavior variability and data limitations.
  • Champion a data-driven culture by establishing experimentation standards, ethical practices, and reproducibility
  • Represent the team’s insights and innovations across the broader data science and product communities within PlayStation.
  • Stay at the forefront of the field by monitoring emerging developments in experimentation, causal inference, and applied machine learning to continuously evolve capabilities.
What We’re Looking For:
  • Master’s Degree or equivalent experience in Applied Math, Economics, Statistics, Computer Science, or related field. Ph.D. or equivalent experience preferred.
  • Strong familiarity with the gaming industry and contemporary gaming experiences.
  • 8+ years of experience in data science, including extensive hands-on work in experimentation, with at least 2+ years in a mentoring or technical leadership capacity.
  • Proven track record of leading experimentation innovation and scaling frameworks within a dynamic business environment.
  • Proficiency in SQL and statistical programming languages (e.g., R or Python), especially for causal inference, experimental analysis, and scalable modeling.
  • Expertise in causal inference techniques and designing both randomized and quasi-experiments.
  • Demonstrated ability to collaborate cross-functionally and influence data strategies that inform business and product decisions.
  • Excellent communication and storytelling skills, especially in conveying complex concepts to non-technical stakeholders.
  • Experience working with modern data engineering and visualization tools (e.g., Airflow, Git, Tableau, MicroStrategy).
  • A strong sense of ownership and an inclusive leadership style that encourages collaboration and innovation.
  • Discretionary bonus opportunity
  • Hybrid Working (within Flexmodes)
  • Private Medical Insurance
  • 25 days holiday per year
  • On Site Gym
  • Free soft drinks
  • Access to cycle garage and showers

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.

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

Apply for this job

*

indicates a required field

First Name *

Last Name *

Email *

Phone

Country *

Phone *

Resume/CV *

Enter manually

Accepted file types: pdf, doc, docx, txt, rtf

Enter manually

Accepted file types: pdf, doc, docx, txt, rtf

LinkedIn Profile

Website

What are your salary expectations? *

What is your current notice period? * Select...

Depending upon where you are currently living, it may be necessary for you to relocate if you are appointed to this role. In order that we can ensure that we promptly provide any appropriate relocation support, please confirm the location at which you currently reside. * Select...

If other, please provide.

Have you previously worked for Sony? * Select...

How did you hear about this job? * Select...

If Employee Referral, please provide the name of the employee who referred you.

Do you wish to be considered for other roles? Select...

Do you hold the right to work in the UK? * Select...

If Other, please provide additional information regarding your right to work in the UK.

UK Diversity & Inclusion - Voluntary Equal Opportunity Monitoring

Sony Interactive Entertainment Europe Limited (‘SIEE’) is committed to ensuring that all job applicants and members of staff are treated equally, without discrimination because of gender, sexual orientation, marital or civil partner status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability or age. Collecting diversity data is intended to help SIEE maintain equal opportunities best practice and identify barriers to workforce equality and diversity. Please read this notification and consent before you decide whether to submit your diversity data in the survey below.

SIEE will treat all survey responses in the strictest confidence, and our personnel with decision-making role in the recruitment process can only see aggregated reports on the results of the survey and cannot allocate these aggregated reports to individual applicants. There is no obligation on you to provide diversity data, SIEE will treat all applicants the same regardless of whether they provide diversity data or not, and any responses to the survey will not affect our decision on your application.

You can withdraw your consent at any time. The withdrawal of your consent does not affect the lawfulness of the processing of your diversity data based on your consent before its withdrawal.

Please tick this box to confirm that you explicitly consent to providing the diversity data below, including the below sensitive information on your racial or ethnic origin, your sexual orientation and your gender identity, and to SIEE using this data as Select...

How would you describe your gender identity? Select...

How would you describe your nationality and/or ethnicity? Select...

Do you identify as transgender? Select...

How would you describe your sexual orientation? Select...

By checking this box, I agree to allow PlayStation Global to retain my data for future opportunities for employment for up to 730 days after the conclusion of consideration of my current application for employment.

By checking this box, I consent to PlayStation Global collecting, storing, and processing my responses to the demographic data surveys above.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Science Manager – Experimentation: Innovation & Research United Kingdom, London

Staff Growth Data Scientist, Monetization

Staff Data Scientist – Experimentation: Innovation & Research

Lead Data Scientist

Data Scientist – CLV & Next Best Action United Kingdom, London

Data Engineer (18 Months FTC)

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.