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Senior Data Scientist

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Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • You will work closely with game developers, data analysts, product managers, and game operations teams.

  • Develop predictive algorithms: Build, train, test, and improve models that support personalisation, player engagement, retention, and monetisation.

  • You will work with colleagues across different teams, contribute to product decisions, and develop solutions which improve gaming experiences.

From the employer’s posting
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.
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.
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Posting record

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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 7, 2026today
Recorded sightings
1

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 7 and day 57.

At Aristocrat, jobs usually come down by about day 41.

From 10,553 similar postings that came down, and 11 of Aristocrat’s. Coming down is not always a hire.

Aristocrat is hiring

18 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Takes jobs down at a usual pace
  • 6% of open jobs were reposted
Hiring record

See how this role fits your experience

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  • Python
  • SQL
  • AWS
  • Azure
  • GCP
Where the posting names them
- 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.
- 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.

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Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 1,411, the most 2,973, and the latest week had 1,815.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original 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.

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Barcelona, Spain

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