Principal Data Scientist

Product Madness ??; Greater London; On-site; GBP 70,000 - 90,000; Full time

Job summary

Product Madness in Greater London is seeking a Principal Data Scientist to enhance gameplay, boost player engagement, and improve business outcomes using advanced data expertise. You will lead high-impact data science projects, deliver innovative machine learning solutions, and partner with game teams to translate analytical results into actionable insights.

The ideal candidate has a PhD or MSc in a quantitative field, extensive experience in data science, and a strong background in software engineering and MLOps. Join us to make significant impacts in the gaming industry!

Qualifications

• 5+ years of professional data science experience.
• Experience delivering at least 3 data or ML products.
• Demonstrated proficiency in clustering, predictive modeling, and Bayesian statistics.

Responsibilities

• Lead data science initiatives from problem framing to impact measurement.
• Build machine learning solutions to enhance player engagement.
• Work with game teams to define success metrics.

Skills

Data Science Expertise

Machine Learning

Statistical Analysis

SQL

Python

MLOps

Big Data Technologies

Education

PhD or MSc in Data Science or related field

Tools

Kafka

Spark

GCP

AWS

Azure

Job description

Are you ready to join a world-class team and make a significant impact on the gaming industry? At Aristocrat, we aim to bring happiness to life through the power of play. We seek a Principal Data Scientist to help us reach our ambitious goals. You will have a vital role in enhancing gameplay, boosting player engagement, and improving business outcomes with your advanced data expertise. This opportunity allows you to work on innovative projects, collaborate with diverse teams, and guide critical initiatives that will develop the future of our leading games.

What You'll Do

• Lead high-impact data science initiatives end-to-end, including problem framing, methodology selection, experiment development, implementation partnership, and impact measurement.
• Build and deliver machine learning and reinforcement learning solutions to improve player engagement, retention, monetization, and operational outcomes.
• Lead the modeling framework for complex systems, guaranteeing comprehensive evaluation and monitoring of causal inference, uplift modeling, sequential decisioning, bandits/reinforcement learning, and forecasting.
• Partner with game teams to define success metrics, guardrails, and decision frameworks, translating analytical results into actionable product and operational actions.
• Define and uphold engineering standards and guidelines for model development, including validation, uncertainty, reproducibility, and bias/quality checks.
• Drive scalable experimentation with A/B and Multi-armed bandit testing frameworks, power analysis, variance reduction, and online-offline alignment.
• Work together with Data Engineering, MLOps, and Game Tech teams to guarantee dependable data foundations, feature accessibility, and model deployment pathways.
• Build internal data products to improve the speed and quality of decision-making, such as AB-test calculators, decision tools, and automated insights.
• Provide technical leadership through building and code reviews, mentoring, and coaching, improving the standard of data science craft across the organization.
• Serve as a reliable collaborator throughout the organization, promoting data-informed decision-making and enabling business units to embrace data products.
• Translate complex analytical insights into actionable recommendations, presenting them to senior leadership to inform critical business decisions and encourage collaborators.

What We Are Seeking

• Education: PhD or MSc in Data Science, Computer Science, Statistics, Physics, Mathematics, or a related quantitative field, or equivalent experience in practice.
• Experience: 5+ years of professional data science experience. You have delivered at least 3 data or ML products from problem definition to production deployment and monitoring.
• Demonstrated proficiency in clustering, predictive modeling, reinforcement learning, and Bayesian statistics.
• Hands‑on experience in software engineering, MLOps, and deploying machine learning models at scale.
• Proficiency in SQL, Python, and familiarity with big data technologies (e.g., Kafka, Spark) and/or cloud platforms (e.g., GCP, AWS, or Azure).
• Industry knowledge: Experience in gaming or digital entertainment is a strong plus.

Travel Expectations

None

Additional Information

At this time, we are unable to sponsor work visas for this position. Candidates must be authorized to work in the job posting location for this position on a full-time basis without the need for current or future visa sponsorship.