The posting
Product Madness builds mobile games enjoyed by players across the globe. We use data, technology, and creativity to develop engaging gaming experiences and make informed business decisions.
Our teams work together to tackle problems, share ideas, and improve our games. Join us and contribute to the development of mobile gaming experiences.
The Role
In the role of a Lead Data Scientist, you will conduct statistical analysis, predictive modelling, and machine learning. You will understand player behaviour, tackle business problems, and improve gaming experiences.
You will handle machine learning initiatives from initial planning through development, evaluation, and implementation. Working with large datasets, you will develop models and analytical tools that support gameplay, player engagement, retention, and monetisation.
You will work closely with game developers, data analysts, product managers, and game operations teams. You will share findings, recommend improvements, and help teams use data to make decisions.
What You'll Do
- Coordinate data science projects: Define business problems, develop hypotheses, select analytical methods, build solutions, and measure results.
- Develop predictive algorithms: Build, train, test, and improve models that support personalisation, player engagement, retention, and monetisation.
- Apply statistical methods: Use statistical analysis, forecasting, simulation, optimisation, and causal inference to answer business questions.
- Design and evaluate experiments: Plan and analyse A/B tests, select metrics, resolve sample sizes, and interpret results.
- Build analytical tools: Develop reusable models, simulations, and tools that help teams make informed decisions.
- Maintain data quality: Prepare and validate datasets, investigate data issues, assess model assumptions, and ensure consistent results.
- Support production solutions: Work with Data Engineering, MLOps, and Game Technology teams to integrate models and analytical solutions into existing systems.
- Share findings and recommendations: Explain analytical results, assumptions, and limitations to collaborators and recommend practical next steps.
- Support team development: Participate in peer reviews, document approaches, share knowledge, and provide guidance to colleagues.
What We're Looking For
- A degree or equivalent experience concentrating on data analysis, Computer Science, Statistics, Mathematics, Physics, or a related field, demonstrating passion for the subjects.
- At least 3 years working in data science, with experience delivering 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 methods.
- Ability to apply forecasting, simulation, or optimisation techniques to business challenges.
- Skills in Python and SQL for data analysis, modelling, and handling extensive data collections.
- 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 cloud platforms such as GCP, AWS, or Azure, and machine learning development environments.
At Product Madness, you will have the opportunity to apply your data science skills to products used by players around the world. You will work with colleagues across different teams, contribute to product decisions, and develop solutions which improve gaming experiences.
We welcome applications from people with different backgrounds and experiences. If your skills align with the role, we encourage you to apply.
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.
Depending on your role and location, you may be eligible for annual bonuses and incentives, health and wellbeing benefits, paid time off, retirement plans, insurance coverage, and other local or statutory benefits.
Specific details about compensation and benefits for this position will be discussed during the recruitment process.
