Data Scientist - Principal

Remote type: Hybrid

Locations: London, United Kingdom

Time type: Full time

Posted on: Posted Today

Job requisition id: R0020855

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.

Why Product Madness

As part of the Aristocrat family, we share their mission of bringing joy to life through the power of play, with a world-class team who creates top-grossing, leading titles in the social casino genre, including Heart of Vegas, Lightning Link, Cashman Casino. With 800 team members across the globe, Product Madness is headquartered in London, with offices in Barcelona, Gdańsk, Lviv, Montreal and a remote team spanning the USA, making us a truly global powerhouse.

We live by our People First principle. Regardless of where, when, or how they work, our team members have opportunities to elevate their careers, and grow alongside us. We take pride in fostering an inclusive culture, where our people are encouraged to be their very best, every day. But don’t just take our word for it. In 2024, we made the Global Inspiring Workplace Awards list, and won a bronze award at the Stevies for Great Employers in the ‘Employer of the Year - Media and Entertainment’ category.

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.