Data Scientist - Experimentation & Measurement

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:

As a Data Scientist within our experimentation and measurement work, you will support how PlayStation tests, measures, and learns across key products and initiatives. You will work alongside senior data scientists and cross-functional partners to deliver robust experimental analysis and build experience in causal and econometric techniques used in real-world settings.

This role is based in London with hybrid working flexibility.

You will:

• 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
• Dental Scheme
• 25 days holiday per year
• On Site Gym
• Subsidised Café
• Free soft drinks
• On site bar
• Access to cycle garage and showers