Data Scientist | Central Analytics

Overview

In this role you translate analytics into actionable marketing investment guidance within King’s Growth Analytics team. You will balance experimentation, modelling and business analysis to explain performance and inform investment decisions. You’ll own defined analytical projects, collaborating with cross-functional partners to connect evidence across measurement approaches. The work focuses on rigorous interpretation and practical application to drive marketing outcomes and player value at scale. This is a chance to grow into broader ownership and influence while shaping measurement-driven decision making.

Responsibilities

• Translate analytical findings into practical recommendations on marketing investment and campaign optimization
• Design and analyze incrementality tests and contribute to MMM and other causal analyses
• Own defined projects from business question to interpretation and stakeholder readout
• Investigate ROI prediction gaps and explain whether to take action or seek more evidence
• Turn evidence into calibration inputs, performance benchmarks, and repeatable analysis tools
• Bridge business and technical questions by framing actionable queries and defining data needs
• Communicate findings clearly to both technical and non-technical audiences and drive process improvements

Key requirements

• Hands-on data science experience with analytics, experimentation, or marketing measurement
• Solid statistical foundation in modelling, hypothesis testing, and causality vs correlation
• Ability to independently deliver scoped analytical work and manage priorities
• Commercial mindset linking analytical results to investment decisions and returns
• Proficiency in Python or R and SQL, with handling of complex datasets and reproducible analyses
• Good communication skills to explain findings and uncertainty without losing practicality
• Growth mindset with openness to feedback and increasing project ownership

• Strong communication
• Curiosity and commercial awareness
• Independent problem-solving with stakeholder collaboration
• Python or R
• SQL
• statistical modelling

…