Data Scientist

the hive; Barcelona; In loco; EUR 65.000 - 95.000; Tempo pieno

Descrizione del lavoro

Product Madness is seeking a Data Scientist to analyze player behaviour, forecast outcomes, and build predictive models for games and monetization. You will collaborate with developers, analysts, and product teams to translate data into actionable insights and personalised experiences for players.

The role involves exploring datasets, developing analytical tools, and contributing to experiments and ML solutions that impact retention and revenue across mobile games.

Competenze

• MSc or PhD in Data Science, Computer Science, Statistics, Physics, Mathematics, or a related quantitative field, or equivalent experience.
• 1+ years of professional experience in data science, machine learning, or quantitative analytics, delivering analytical or modelling projects.
• Strong foundation in statistics, probability, descriptive analysis, and statistical inference.
• Experience with exploratory data analysis, data preparation, and large datasets.
• Experience developing and evaluating predictive or machine learning models (regression, classification, clustering).
• Understanding of statistical modelling, forecasting, and simulation techniques.
• Familiarity with hypothesis testing, A/B testing, and experimental analysis.
• Proficiency in Python for data analysis with libraries such as pandas, NumPy, scikit-learn.
• Ability to write SQL queries to extract and transform data.
• Basic understanding of software development practices (version control, testing, documentation).
• Experience using AI assistants to support coding and analysis with validation.

Mansioni

• Explore business challenges, develop hypotheses, and deliver data-driven solutions with guidance.
• Develop, test, and improve predictive algorithms and AI techniques to enhance player experiences, engagement, retention, and revenue.
• Apply statistics, forecasting, predictive modelling, and simulation to understand player behaviour and business performance.
• Support A/B testing by selecting metrics, analysing results, and sharing findings for decisions.
• Create analytical models, simulations, and tools for informed decision-making.
• Prepare and explore large datasets to uncover trends and insights for business goals.
• Collaborate with senior data scientists, Data Engineering, and MLOps to deploy models into processes.
• Share findings with stakeholders, explain insights and limitations, and offer practical recommendations.
• Document work and participate in peer reviews to develop technical skills.

Conoscenze

Python

SQL

Statistics

Machine learning

Data visualization

Experimentation

Communication

Formazione

MSc or PhD in Data Science or related

Strumenti

pandas

NumPy

scikit-learn

Descrizione del lavoro

At Product Madness, we create mobile games that bring entertainment to players around the world. Data plays an important role in understanding player needs, improving gaming experiences, and making informed business decisions.

Join our collaborative team, where your ideas and expertise will help us explore new opportunities, solve meaningful challenges, and shape the future of mobile gaming.

The Role

As a Data Scientist at Product Madness, you will use data analysis, forecasting, and predictive modelling to better understand player behaviour, solve business challenges, and improve gaming experiences.

You will contribute to projects dedicated to player involvement, retention, and revenue. You will also help develop analytical tools and machine learning solutions that support informed decisions and create more personalised experiences for our players.

Working with a variety of datasets, you will take ownership of clearly defined analytical and modelling tasks while learning from experienced data scientists on more complex projects. You will collaborate with game developers, data analysts, product managers, and game operations teams to translate data into meaningful insights and practical improvements.

What You'll Do

• Explore business challenges, develop hypotheses, choose suitable analytical methods, and deliver data-driven solutions with support from experienced colleagues when needed.
• Develop, test, and improve predictive algorithms and artificial intelligence techniques to improve player experiences, engagement, retention, and revenue.
• Apply statistical analysis, forecasting, predictive modelling, and simulation to understand player behaviour and business performance.
• Support A/B testing and experiments by selecting relevant metrics, analysing results, and sharing findings that guide business decisions.
• Create analytical models, simulations, and tools that help teams make informed decisions and find opportunities for improvement.
• Prepare, validate, and explore large datasets to uncover trends, patterns, and insights that support business goals.
• Work with senior data scientists, Data Engineering, and MLOps teams to develop and integrate analytical models and machine learning solutions into business processes.
• Share findings with collaborators, explain key insights and limitations, and offer practical recommendations.
• Contribute to a supportive team environment by documenting your work, participating in peer reviews, sharing knowledge, and developing your technical skills.

What We're Looking For

• MSc or PhD in Data Science, Computer Science, Statistics, Physics, Mathematics, or a related quantitative field, or possessing equivalent experience.
• 1+ years of professional experience in data science, machine learning, or quantitative analytics, with practical experience delivering analytical or modelling projects.
• Strong foundation in statistics, probability, descriptive analysis, and statistical inference.
• Practical experience in exploratory data analysis, data preparation, and working with large datasets.
• Experience developing and evaluating predictive or machine learning models, including regression, classification, or clustering.
• Understanding of statistical modelling, forecasting, and simulation techniques.
• Familiarity with hypothesis testing, split testing, and experimental analysis.
• Working knowledge of Python for data analysis and modelling, including common libraries such as pandas, NumPy, and scikit-learn.
• Ability to write SQL queries to extract, join, transform, and aggregate data.
• Basic understanding of software development practices, including version control, testing, and documentation.
• Experience using AI assistants to support coding, analysis, and other professional tasks, with appropriate validation of outputs.

If you’re passionate about demonstrating data science to create exceptional gaming experiences and are ready to lead data products to success, we want to hear from you. Join Product Madness and contribute to the evolution of mobile gaming!

This job description may have been reviewed and enhanced using AI-assisted tools to improve clarity, consistency, and inclusivity. All final content, role requirements and hiring decisions remain subject to human review and approval by Aristocrat.

Compensation Philosophy

We offer a comprehensive pay and benefits package designed to stay competitive in the market, support your wellbeing, and recognise your contribution to our success. Our approach is underpinned by a pay-for-performance belief in rewarding individual impact. Your specific compensation package will be determined by factors such as your skills, experience, qualifications, and location.

Specific details about compensation and benefits for this position will be discussed during the recruitment process.

• annual bonuses and incentives
• health and wellbeing benefits
• paid time off
• retirement plans
• insurance coverage
• other local or statutory benefits