Data Scientist (AI)

Location: Barcelona, Spain; hybrid workplace

Company

Product Madness, part of hirify.global, develops mobile games and uses data to improve player experiences and business decisions.

What you will do

• Explore business challenges, develop hypotheses, select analytical methods, and deliver data-driven solutions.
• Develop, test, and improve predictive algorithms, machine learning solutions, and AI techniques for player engagement, retention, revenue, and personalisation.
• Apply statistical analysis, forecasting, predictive modelling, and simulation to understand player behaviour and business performance.
• Support A/B tests and experiments by selecting metrics, analysing results, and communicating findings.
• Prepare, validate, and explore large datasets; create analytical models, simulations, and tools that support business decisions.
• Collaborate with data scientists, Data Engineering, MLOps, game developers, data analysts, product managers, and game operations teams; document work and participate in peer reviews.

Requirements

• MSc or PhD in Data Science, Computer Science, Statistics, Physics, Mathematics, or a related quantitative field, or equivalent experience.
• At least 1 year of professional experience in data science, machine learning, or quantitative analytics, including delivery of analytical or modelling projects.
• Strong foundation in statistics, probability, descriptive analysis, and statistical inference.
• Practical experience with exploratory data analysis, data preparation, and large datasets.
• Experience developing and evaluating predictive or machine learning models, including regression, classification, or clustering.
• Understanding of statistical modelling, forecasting, simulation, hypothesis testing, split testing, and experimental analysis.
• Working knowledge of Python for data analysis and modelling, including pandas, NumPy, and scikit-learn.
• Ability to write SQL queries for extracting, joining, transforming, and aggregating data.
• Basic understanding of software development practices, including version control, testing, and documentation.
• Experience using AI assistants for coding, analysis, and other professional tasks, with appropriate validation of outputs.

Culture & Benefits

• Collaborative environment with support from experienced data scientists.
• Opportunities to learn through complex analytical and modelling projects, peer reviews, knowledge sharing, and technical development.
• Depending on role and location, benefits may include annual bonuses and incentives, health and wellbeing benefits, paid time off, retirement plans, insurance coverage, and local or statutory benefits.
• Compensation is determined by skills, experience, qualifications, and location; specific details are discussed during recruitment.