Principal Data Scientist
Aristocrat
full-time
Posted on:
Location Type: Hybrid
Location: London • United Kingdom
Visit company websiteExplore more
Job Level
About the role
- 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.
Requirements
- PhD or MSc in Data Science, Computer Science, Statistics, Physics, Mathematics, or a related quantitative field, or equivalent experience in practice.
- 5+ years of professional data science experience.
- At least 3 data or ML products from problem definition to production deployment and monitoring.
- 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).
Benefits
- Health insurance
- 401(k) matching
- Paid time off
- Flexible work arrangements
- Professional development opportunities
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data sciencemachine learningreinforcement learningclusteringpredictive modelingBayesian statisticsA/B testingmulti-armed bandit testingmodel validationcausal inference
Soft Skills
technical leadershipcollaborationmentoringcoachingcommunicationproblem framingtranslating analytical resultsdecision-makingimpact measurementorganizational skills
Certifications
PhD in Data ScienceMSc in Data SciencePhD in Computer ScienceMSc in Computer SciencePhD in StatisticsMSc in StatisticsPhD in PhysicsMSc in PhysicsPhD in MathematicsMSc in Mathematics