At a Glance
- Tasks: Support PlayStation's experimentation and measurement efforts through data analysis and collaboration.
- Company: Join the innovative team at PlayStation, a leader in gaming and entertainment.
- Benefits: Enjoy hybrid working, private medical insurance, 25 days holiday, and more perks.
- Why this job: Make an impact in gaming by using data to drive decisions and enhance player experiences.
- Qualifications: Early career experience in data science or analytics with a quantitative degree.
- Other info: Collaborative environment with opportunities for growth and mentorship.
The predicted salary is between 36000 - 60000 ÂŁ per year.
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.
Data Scientist – Data Science Analytics and Enablement (DSAE)
Our Data Science Analytics and Enablement (DSAE) team inspires PlayStation 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.
DSAE is looking to recruit talented, highly driven individuals who have excelled in previous roles and are looking for a new challenge in a dynamic and rewarding environment.
What You’ll Be Doing:
- Support the design, execution, and analysis of experiments (e.g. A/B tests), including metric definition, validation, and interpretation
- Apply statistical testing techniques to evaluate experimental outcomes and quantify impact
- Assist with causal analysis where full randomisation is not feasible, using established approaches such as pre/post analysis, matched cohorts, or difference‑in‑differences, under guidance
- Contribute to exploratory econometric‑style analyses to better understand drivers of player behaviour and commercial outcomes
- Partner with engineering, analytics, and product teams to ensure accurate experiment setup and clean data capture
- Monitor live experiments and analyses, flagging data quality issues or unexpected results
- Produce clear analysis outputs, visualisations, and summaries that explain results, assumptions, and limitations
- Contribute to experiment readouts and stakeholder updates with support from senior team members
- Follow established experimentation standards and contribute to documentation, tooling, or reusable analysis patterns
- Continue to build skills in experimentation, causal inference, and applied analytics through hands‑on work and mentorship
What We’re Looking For:
- Early career experience in data science, analytics, or a related quantitative role
- Degree (or equivalent experience) in a quantitative field such as Statistics, Economics, Applied Mathematics, Computer Science, or similar
- Proven foundation in statistics, including hypothesis testing and basic experimental analysis
- Familiarity with A/B testing concepts and an interest in causal inference and econometric approaches
- Proficiency in SQL and Python (or R) for data querying, preparation, and analysis
- Ability to clearly communicate analytical findings to non‑technical partners
- Strong attention to detail and commitment to analytical rigor and data quality
- Collaborative, proactive attitude with comfort working across product, engineering, and analytics teams
- Curiosity and motivation to develop deeper expertise in experimentation, causal analysis, and measurement over time
- Exposure to digital products, e‑commerce, gaming, or customer lifecycle analytics is a plus, but not required
- Knowledge of machine learning approaches is a plus, but not required
Benefits:
- 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.
Data Scientist - Experimentation & Measurement New United Kingdom, London employer: PlayStation
Contact Detail:
PlayStation Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Experimentation & Measurement New United Kingdom, London
✨Tip Number 1
Network like a pro! Reach out to current or former employees at PlayStation on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by brushing up on your A/B testing knowledge and statistical techniques. Be ready to discuss how you've applied these in past projects. We want to see your analytical skills in action!
✨Tip Number 3
Show off your passion for gaming and data! When you talk about your experiences, link them back to how they can benefit PlayStation. Let us know why you're excited about this role and the company.
✨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 serious about joining the PlayStation family.
We think you need these skills to ace Data Scientist - Experimentation & Measurement New United Kingdom, London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with A/B testing, SQL, and Python, and don’t forget to mention any relevant projects or coursework that showcase your skills in experimentation and measurement.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data science and how your background aligns with PlayStation’s mission. Be sure to mention your curiosity for innovation and your collaborative spirit.
Showcase Your Analytical Skills: In your application, provide examples of how you've applied statistical techniques in real-world scenarios. Whether it's through coursework or previous jobs, demonstrate your ability to analyse data and communicate findings clearly.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, you’ll find all the details you need about the role and our team!
How to prepare for a job interview at PlayStation
✨Know Your Stats
Brush up on your statistics knowledge, especially hypothesis testing and experimental analysis. Be ready to discuss how you’ve applied these concepts in previous roles or projects, as this will show your foundational understanding and readiness for the role.
✨A/B Testing Familiarity
Make sure you understand A/B testing concepts inside out. Prepare to talk about any past experiences where you've designed or analysed experiments, and be ready to explain the outcomes and what you learned from them.
✨SQL and Python Proficiency
Since proficiency in SQL and Python (or R) is key for this role, practice your coding skills before the interview. You might be asked to solve a problem on the spot, so being comfortable with data querying and analysis will give you an edge.
✨Communicate Clearly
Prepare to explain complex analytical findings in simple terms. Think of examples where you’ve had to present data insights to non-technical stakeholders, as this will demonstrate your ability to bridge the gap between data science and business needs.