Growth Data Scientist

November 8, 2026

Hybrid

Middle

Barcelona, Spain

Indeed

Description

The role centers on player acquisition strategy for mobile gaming, advising the UA team on budget planning and channel tactics through data analysis and modelling. It covers statistical analysis, causal inference, machine learning, time-series modelling and forecasting models to understand user behavior and assess marketing channel efficiency. The Data Scientist also translates complex findings into clear insights for technical and non-technical collaborators and works with Data Analytics and Engineering on reliable data foundations.

Responsibilities

Counsel the UA team regarding budget planning and channel tactics based on comprehensive data analysis and modelling
Apply statistical analysis, causal inference, machine learning, and time-series modelling to understand user behavior and assess marketing channel efficiency
Proactively identify areas of improvement; build and run analyses and models that lead to actionable recommendations
Build and maintain forecasting models to support UA planning and decision-making
Translate complex analytical findings into clear, compelling insights for both technical and non-technical collaborators
Collaborate with Data Analytics and Engineering teams to ensure reliable data foundations and feature availability
Learn from and share ideas with a diverse, globally distributed team of data scientists

Requirements

Degree in Mathematics, Statistics, Economics, Computer Science, or a similar quantitative field, or equivalent experience
Professional data science experience, with a consistent track record of delivering end-to-end data or ML projects
Practical experience applying analytical techniques to address real business challenges, ideally in a marketing, growth, or digital environment
Experience in gaming or digital entertainment is a strong plus
Proficiency in Python and SQL
Experience building forecasting and time-series models
Familiarity with causal inference methods (e.g. diff-in-diff, regression discontinuity, uplift modelling)
Knowledge of statistical analysis and experimentation (A/B testing, significance testing)
Experience with data visualization tools and communicating analytical results clearly
Pragmatic approach to problem-solving, favoring practical solutions
Comfortable working with ambiguity and switching context as business priorities evolve
Curious and proactive, with a deep understanding of problems before jumping to solutions

Conditions

Full-time employment
Hybrid schedule with three days per week in the Barcelona office
Paid time off
Annual bonuses and incentives may be offered depending on role and location
Health and wellbeing benefits, retirement plans and insurance coverage may be offered