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.