Senior Data Scientist (Mobile Gaming)

Location: Barcelona, Spain; hybrid workplace

Company

Product Madness develops mobile games and uses data, technology, and creativity to improve gaming experiences and business decisions.

What you will do

• Coordinate data science projects by defining business problems, forming hypotheses, selecting methods, building solutions, and measuring results.
• Build, train, test, and improve predictive algorithms supporting personalisation, player engagement, retention, and monetisation.
• Apply statistical analysis, forecasting, simulation, optimisation, and causal inference to business questions.
• Design and evaluate A/B tests, including metric selection, sample-size assessment, and result interpretation.
• Prepare and validate datasets, investigate data issues, assess model assumptions, and maintain consistent analytical results.
• Collaborate with data engineering, MLOps, game technology, development, analytics, product, and game operations teams to integrate solutions and communicate recommendations.

Requirements

• Degree or equivalent experience in data analysis, computer science, statistics, mathematics, physics, or a related field.
• At least 3 years of experience in data science, including delivery of analytical or machine learning projects.
• Knowledge of statistics, probability, and data analysis.
• Ability to develop, build, assess, and evaluate predictive and machine learning models.
• Experience with A/B testing, experimental design, hypothesis testing, and causal inference.
• Ability to apply forecasting, simulation, or optimisation techniques to business challenges.
• Proficiency in Python and SQL for data analysis, modelling, and handling extensive datasets.
• Knowledge of software development practices, including version control, testing, and documentation.
• Familiarity with AI tools and generative AI applications.
• Understanding of machine learning deployment and monitoring, including collaboration with engineering teams.

Nice to have

• Experience in mobile gaming, digital entertainment, or other consumer-focused products.
• Knowledge of recommender systems, reinforcement learning, Bayesian modelling, stochastic simulation, or time-series forecasting.
• Experience building analytical tools or applications for business teams.
• Familiarity with GCP, AWS, Azure, or machine learning development environments.

Culture & Benefits

• Collaborative work across game development, analytics, product, operations, data engineering, MLOps, and game technology teams.
• Opportunities to contribute to products used by players worldwide and to product decisions based on data.
• Applications are welcomed from people with different backgrounds and experiences.
• Depending on role and location, benefits may include annual bonuses and incentives, health and wellbeing benefits, paid time off, retirement plans, insurance, and local statutory benefits.
• Compensation is determined according to skills, experience, qualifications, and location; details are discussed during recruitment.