Senior Data Scientist (Loyalty Analytics)

What you'll do

• Develop analytical and machine-learning solutions to improve member acquisition, engagement, retention, and lifetime value.

• Build segmentation, propensity, recommendation, uplift, and optimization models for loyalty use cases.

• Design and analyze experiments, including test-and-control frameworks and causal-impact measurement.

• Translate business questions into rigorous analytical approaches and actionable recommendations.

• Partner with product managers, engineers, analysts, marketers, and other data scientists to define priorities and deliver production-ready solutions.

• Establish success metrics and measurement frameworks for loyalty initiatives.

• Communicate findings clearly to technical and non-technical audiences, including senior stakeholders.

• Promote high standards for data quality, reproducibility, model governance, and responsible use of customer data.

• Contribute to the evolution of the organisation's loyalty data platform and data products.

What you'll bring

• Significant experience in data science, advanced analytics, or a closely related quantitative field.

• Strong programming skills in Python and SQL.

• Practical experience with statistical modelling, machine learning, experimentation, and causal inference.

• Experience working with customer, marketing, CRM, membership, rewards, or personalization data.

• Ability to work with large-scale, complex, and evolving data environments.

• Strong product sense and the ability to connect analytical outputs to customer and commercial outcomes.

• Excellent written and verbal communication skills.

• A collaborative, pragmatic approach and a track record of delivering outcomes through cross-functional partnerships.

Requirements

Preferred qualifications

• Experience with loyalty, travel, marketplaces, subscriptions, rewards, or customer lifecycle analytics.

• 8+ years of experience in a similar analytical role.

• Experience developing models that influence customer journeys or marketing decisions.

• Experience taking models from prototyping through deployment, monitoring, and iteration.

• Graduate degree in statistics, computer science, operations research, economics, mathematics, or a related quantitative discipline.

Benefits

· Competitive salary and performance-based bonuses.

· Comprehensive insurance plans.

· Collaborative and supportive work environment.

· Chance to learn and grow with a talented team.

· A positive and fun work environment.